Harvesting Water from Air with High-Capacity, Stable Furan-Based Metal-Organic Frameworks.

We synthesized two isoreticular furan-based metal-organic frameworks (MOFs), MOF-LA2-1(furan) and MOF-LA2-2(furan) with rod-like secondary building units (SBUs) featuring 1D channels, as sorbents for atmospheric water harvesting (LA = long arm). These aluminum-based MOFs demonstrated a combination of high water uptake and stability, exhibiting working capacities of 0.41 and 0.48 gwater/gMOF (under isobaric conditions of 1.70 kPa), respectively. Remarkably, both MOFs showed a negligible loss in water uptake after 165 adsorption-desorption cycles. These working capacities rival that of MOF-LA2-1(pyrazole), which has a working capacity of 0.55 gwater/gMOF. The current MOFs stand out for their high water stability, as evidenced by 165 cycles of water uptake and release. MOF-LA2-2(furan) is the first aluminum MOF to employ a double 'long arm' extension strategy, which is confirmed through single-crystal X-ray diffraction (SCXRD). The MOFs were synthesized by using a straightforward synthesis route. This study offers valuable insights into the design of durable, water-stable MOFs and underscores their potential for efficient water harvesting.

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

We construct a data set of metal-organic framework (MOF) linkers and employ a fine-tuned GPT assistant to propose MOF linker designs by mutating and modifying the existing linker structures. This strategy allows the GPT model to learn the intricate language of chemistry in molecular representations, thereby achieving an enhanced accuracy in generating linker structures compared with its base models. Aiming to highlight the significance of linker design strategies in advancing the discovery of water-harvesting MOFs, we conducted a systematic MOF variant expansion upon state-of-the-art MOF-303 utilizing a multidimensional approach that integrates linker extension with multivariate tuning strategies. We synthesized a series of isoreticular aluminum MOFs, termed Long-Arm MOFs (LAMOF-1 to LAMOF-10), featuring linkers that bear various combinations of heteroatoms in their five-membered ring moiety, replacing pyrazole with either thiophene, furan, or thiazole rings or a combination of two. Beyond their consistent and robust architecture, as demonstrated by permanent porosity and thermal stability, the LAMOF series offers a generalizable synthesis strategy. Importantly, these 10 LAMOFs establish new benchmarks for water uptake (up to 0.64 g g-1) and operational humidity ranges (between 13 and 53%), thereby expanding the diversity of water-harvesting MOFs.

ChatGPT Research Group for Optimizing the Crystallinity of MOFs and COFs.

We leveraged the power of ChatGPT and Bayesian optimization in the development of a multi-AI-driven system, backed by seven large language model-based assistants and equipped with machine learning algorithms, that seamlessly orchestrates a multitude of research aspects in a chemistry laboratory (termed the ChatGPT Research Group). Our approach accelerated the discovery of optimal microwave synthesis conditions, enhancing the crystallinity of MOF-321, MOF-322, and COF-323 and achieving the desired porosity and water capacity. In this system, human researchers gained assistance from these diverse AI collaborators, each with a unique role within the laboratory environment, spanning strategy planning, literature search, coding, robotic operation, labware design, safety inspection, and data analysis. Such a comprehensive approach enables a single researcher working in concert with AI to achieve productivity levels analogous to those of an entire traditional scientific team. Furthermore, by reducing human biases in screening experimental conditions and deftly balancing the exploration and exploitation of synthesis parameters, our Bayesian search approach precisely zeroed in on optimal synthesis conditions from a pool of 6 million within a significantly shortened time scale. This work serves as a compelling proof of concept for an AI-driven revolution in the chemistry laboratory, painting a future where AI becomes an efficient collaborator, liberating us from routine tasks to focus on pushing the boundaries of innovation.

A GPT-4 Reticular Chemist for Guiding MOF Discovery.

We present a new framework integrating the AI model GPT-4 into the iterative process of reticular chemistry experimentation, leveraging a cooperative workflow of interaction between AI and a human researcher. This GPT-4 Reticular Chemist is an integrated system composed of three phases. Each of these utilizes GPT-4 in various capacities, wherein GPT-4 provides detailed instructions for chemical experimentation and the human provides feedback on the experimental outcomes, including both success and failures, for the in-context learning of AI in the next iteration. This iterative human-AI interaction enabled GPT-4 to learn from the outcomes, much like an experienced chemist, by a prompt-learning strategy. Importantly, the system is based on natural language for both development and operation, eliminating the need for coding skills, and thus, make it accessible to all chemists. Our collaboration with GPT-4 Reticular Chemist guided the discovery of an isoreticular series of MOFs, with each synthesis fine-tuned through iterative feedback and expert suggestions. This workflow presents a potential for broader applications in scientific research by harnessing the capability of large language models like GPT-4 to enhance the feasibility and efficiency of research activities.

Monolithic Zirconium-Based Metal-Organic Frameworks for Energy-Efficient Water Adsorption Applications.

Space cooling and heating, ventilation, and air conditioning (HVAC) accounts for roughly 10% of global electricity use and are responsible for ca. 1.13 gigatonnes of CO2 emissions annually. Adsorbent-based HVAC technologies have long been touted as an energy-efficient alternative to traditional refrigeration systems. However, thus far, no suitable adsorbents have been developed which overcome the drawbacks associated with traditional sorbent materials such as silica gels and zeolites. Metal-organic frameworks (MOFs) offer order-of-magnitude improvements in water adsorption and regeneration energy requirements. However, the deployment of MOFs in HVAC applications has been hampered by issues related to MOF powder processing. Herein, three high-density, shaped, monolithic MOFs (UiO-66, UiO-66-NH2 , and Zr-fumarate) with exceptional volumetric gas/vapor uptake are developed-solving previous issues in MOF-HVAC deployment. The monolithic structures across the mesoporous range are visualized using small-angle X-ray scattering and lattice-gas models, giving accurate predictions of adsorption characteristics of the monolithic materials. It is also demonstrated that a fragile MOF such as Zr-fumarate can be synthesized in monolithic form with a bulk density of 0.76 gcm-3 without losing any adsorption performance, having a coefficient of performance (COP) of 0.71 with a low regeneration temperature (≤ 100 °C).

Homochiral Porous Metal-Organic Polyhedra with Multiple Kinds of Vertices.

Metal-organic polyhedra featuring non-Archimedean/Platonic architectures with multiple kinds of vertices have aroused great attention for their fascinating structures and properties but are yet challenging to achieve. Here, we report a combinatorial strategy to make such nonclassic polyhedral cages by combining kinetically labile metal ions with non-planar organic linkers instead of the usual only inert metal centers and planar ligands. This facilitates the synthesis of an enantiopure twisted tetra(3-pyridyl)-based TADDOL (TADDOL = tetraaryl-1,3-dioxolane-4,5-dimethanol) ligand (L) capable of binding Ni(II) ions to produce a regular convex cage, Ni6L8, with two mixed metal/organic vertices and three rarely reported concave cages Ni14L8, Ni18L12, and Ni24L16 with three or four mixed vertices. Each of the cages has an amphiphilic cavity decorated with chiral dihydroxyl functionalities and packs into a three-dimensional structure. The enantioselective adsorption and separation performances of the cages are strongly dependent on their pore structure features. Particularly, Ni14L8 and Ni18L12 with wide openings can be solid adsorbents for the adsorptive and solid-phase extractive separation of a variety of racemic spirodiols with up to 98% ee, whereas Ni6L8 and Ni24L16 with smaller pore apertures cannot adsorb the racemates. The combination of single-crystal X-ray diffraction analysis of the host-guest adduct and GCMC simulation indicates that the enantiospecific recognition capabilities originate from the well-organized chiral inner sphere as well as multiple interactions within the chiral microenvironment. This work therefore provides an attractive strategy for the rational design of polyhedral cages, showing geometrically fascinating structures with properties different from those of classic assemblies.

Densified HKUST-1 Monoliths as a Route to High Volumetric and Gravimetric Hydrogen Storage Capacity.

We are currently witnessing the dawn of hydrogen (H2) economy, where H2 will soon become a primary fuel for heating, transportation, and long-distance and long-term energy storage. Among diverse possibilities, H2 can be stored as a pressurized gas, a cryogenic liquid, or a solid fuel via adsorption onto porous materials. Metal-organic frameworks (MOFs) have emerged as adsorbent materials with the highest theoretical H2 storage densities on both a volumetric and gravimetric basis. However, a critical bottleneck for the use of H2 as a transportation fuel has been the lack of densification methods capable of shaping MOFs into practical formulations while maintaining their adsorptive performance. Here, we report a high-throughput screening and deep analysis of a database of MOFs to find optimal materials, followed by the synthesis, characterization, and performance evaluation of an optimal monolithic MOF (monoMOF) for H2 storage. After densification, this monoMOF stores 46 g L-1 H2 at 50 bar and 77 K and delivers 41 and 42 g L-1 H2 at operating pressures of 25 and 50 bar, respectively, when deployed in a combined temperature-pressure (25-50 bar/77 K → 5 bar/160 K) swing gas delivery system. This performance represents up to an 80% reduction in the operating pressure requirements for delivering H2 gas when compared with benchmark materials and an 83% reduction compared to compressed H2 gas. Our findings represent a substantial step forward in the application of high-density materials for volumetric H2 storage applications.

How Reproducible are Surface Areas Calculated from the BET Equation?

Porosity and surface area analysis play a prominent role in modern materials science. At the heart of this sits the Brunauer-Emmett-Teller (BET) theory, which has been a remarkably successful contribution to the field of materials science. The BET method was developed in the 1930s for open surfaces but is now the most widely used metric for the estimation of surface areas of micro- and mesoporous materials. Despite its widespread use, the calculation of BET surface areas causes a spread in reported areas, resulting in reproducibility problems in both academia and industry. To prove this, for this analysis, 18 already-measured raw adsorption isotherms were provided to sixty-one labs, who were asked to calculate the corresponding BET areas. This round-robin exercise resulted in a wide range of values. Here, the reproducibility of BET area determination from identical isotherms is demonstrated to be a largely ignored issue, raising critical concerns over the reliability of reported BET areas. To solve this major issue, a new computational approach to accurately and systematically determine the BET area of nanoporous materials is developed. The software, called "BET surface identification" (BETSI), expands on the well-known Rouquerol criteria and makes an unambiguous BET area assignment possible.

The development of a comprehensive toolbox based on multi-level, high-throughput screening of MOFs for CO/N2 separations.

The separation of CO/N2 mixtures is a challenging problem in the petrochemical sector due to the very similar physical properties of these two molecules, such as size, molecular weight and boiling point. To solve this and other challenging gas separations, one requires a holistic approach. The complexity of a screening exercise for adsorption-based separations arises from the multitude of existing porous materials, including metal-organic frameworks. Besides, the multivariate nature of the performance criteria that needs to be considered when designing an optimal adsorbent and a separation process - i.e. an optimal material requires fulfillment of several criteria simultaneously - makes the screening challenging. To address this, we have developed a multi-scale approach combining high-throughput molecular simulation screening, data mining and advanced visualization, as well as process system modelling, backed up by experimental validation. We have applied our recent advances in the engineering of porous materials' morphology to develop advanced monolithic structures. These conformed, shaped monoliths can be used readily in industrial applications, bringing a valuable strategy for the development of advanced materials. This toolbox is flexible enough to be applied to multiple adsorption-based gas separation applications.

Formulation of Metal-Organic Framework-Based Drug Carriers by Controlled Coordination of Methoxy PEG Phosphate: Boosting Colloidal Stability and Redispersibility.

Metal-organic framework nanoparticles (nanoMOFs) have been widely studied in biomedical applications. Although substantial efforts have been devoted to the development of biocompatible approaches, the requirement of tedious synthetic steps, toxic reagents, and limitations on the shelf life of nanoparticles in solution are still significant barriers to their translation to clinical use. In this work, we propose a new postsynthetic modification of nanoMOFs with phosphate-functionalized methoxy polyethylene glycol (mPEG-PO3) groups which, when combined with lyophilization, leads to the formation of redispersible solid materials. This approach can serve as a facile and general formulation method for the storage of bare or drug-loaded nanoMOFs. The obtained PEGylated nanoMOFs show stable hydrodynamic diameters, improved colloidal stability, and delayed drug-release kinetics compared to their parent nanoMOFs. Ex situ characterization and computational studies reveal that PEGylation of PCN-222 proceeds in a two-step fashion. Most importantly, the lyophilized, PEGylated nanoMOFs can be completely redispersed in water, avoiding common aggregation issues that have limited the use of MOFs in the biomedical field to the wet form-a critical limitation for their translation to clinical use as these materials can now be stored as dried samples. The in vitro performance of the addition of mPEG-PO3 was confirmed by the improved intracellular stability and delayed drug-release capability, including lower cytotoxicity compared with that of the bare nanoMOFs. Furthermore, z-stack confocal microscopy images reveal the colocalization of bare and PEGylated nanoMOFs. This research highlights a facile PEGylation method with mPEG-PO3, providing new insights into the design of promising nanocarriers for drug delivery.

Monolithic metal-organic frameworks for carbon dioxide separation.

Carbon dioxide (CO2) is both a primary contributor to global warming and a major industrial impurity. Traditional approaches to carbon capture involve corrosive and energy-intensive processes such as liquid amine absorption. Although adsorptive separation has long been a promising alternative to traditional processes, up to this point there has been a lack of appropriate adsorbents capable of capturing CO2 whilst maintaining low regeneration energies. In the context of CO2 capture, metal-organic frameworks (MOFs) have gained much attention in the past two decades as potential materials. Their tuneable nature allows for precise control over the pore size and chemistry, which allows for the tailoring of their properties for the selective adsorption of CO2. While many candidate materials exist, the amount of research into material shaping for use in industrial processes has been limited. Traditional shaping strategies such as pelletisation involve the use of binders and/or mechanical processes, which can have a detrimental impact on the adsorption properties of the resulting materials or can result in low-density structures with low volumetric adsorption capacities. Herein, we demonstrate the use of a series of monolithic MOFs (monoUiO-66, monoUiO-66-NH2 & monoHKUST-1) for use in gas separation processes.

Continuous Fixed-Bed Column Studies on Congo Red Dye Adsorption-Desorption Using Free and Immobilized Nelumbo nucifera Leaf Adsorbent.

The adsorption of Congo red (CR), an azo dye, from aqueous solution using free and immobilized agricultural waste biomass of Nelumbo nucifera (lotus) has been studied separately in a continuous fixed-bed column operation. The N. nucifera leaf powder adsorbent was immobilized in various polymeric matrices and the maximum decolorization efficiency (83.64%) of CR occurred using the polymeric matrix sodium silicate. The maximum efficacy (72.87%) of CR dye desorption was obtained using the solvent methanol. Reusability studies of free and immobilized adsorbents for the decolorization of CR dye were carried out separately in three runs in continuous mode. The % color removal and equilibrium dye uptake of the regenerated free and immobilized adsorbents decreased significantly after the first cycle. The decolorization efficiencies of CR dye adsorption were 53.66% and 43.33%; equilibrium dye uptakes were 1.179 mg g-1 and 0.783 mg g-1 in the third run of operation with free and immobilized adsorbent, respectively. The column experimental data fit very well to the Thomas and Yoon-Nelson models for the free and immobilized adsorbent with coefficients of correlation R2 ≥ 0.976 in various runs. The study concludes that free and immobilized N. nucifera can be efficiently used for the removal of CR from synthetic and industrial wastewater in a continuous flow mode. It makes a substantial contribution to the development of new biomass materials for monitoring and remediation of toxic dye-contaminated water resources.

In Silico Discovery of Covalent Organic Frameworks for Carbon Capture.

We screen a database of more than 69 000 hypothetical covalent organic frameworks (COFs) for carbon capture using parasitic energy as a metric. To compute CO2-framework interactions in molecular simulations, we develop a genetic algorithm to tune the charge equilibration method and derive accurate framework partial charges. Nearly 400 COFs are identified with parasitic energy lower than that of an amine scrubbing process using monoethanolamine; more than 70 are better performers than the best experimental COFs and several perform similarly to Mg-MOF-74. We analyze the effect of pore topology on carbon capture performance to guide the development of improved carbon capture materials.

Ab Initio Flexible Force Field for Metal-Organic Frameworks Using Dummy Model Coordination Bonds.

We present force fields developed from periodic density functional theory (DFT) calculations that can be used in classical molecular simulations to model M-MOF-74 (M = Co, Fe, Mg, Mn, Ni, Zn) and its extended linker analogs. Our force fields are based on cationic dummy models (CDMs). These dummy models simplify the methodology required to tune the parameters and improve the accuracy of the force fields. We used our force fields to compare mechanical properties across the M-MOF-74 series and determine that increasing the size of the linker decreases the framework rigidity. In addition, we applied our force fields to an extended linker analog of Mg-MOF-74 and characterized the free energy of a previously reported deformation pattern in which the one-dimensional hexagonal channels of the framework become irregular. The free energy profiles confirm that the deformation is adsorbate induced and impossible to access solely by a pressure stimulus. On the basis of our results, we conclude that the force fields presented here and others that may be developed using our methodology are transferable across metal-organic framework series that share a metal center topology. Finally, we believe that these force fields have the potential to be adapted for the study of complex problems in MOF chemistry, including defects and crystal growth, that have thus far been beyond the scope of classical molecular simulations.