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We use prompt engineering to guide ChatGPT in the automation of text mining of metal–organic framework (MOF) synthesis conditions from diverse formats and styles of the scientific literature. This effectively mitigates ChatGPT’s tendency to hallucinate information, an issue that previously made the use of large language models (LLMs) in scientific fields challenging. Our approach involves the development of a workflow implementing three different processes for text mining, programmed by ChatGPT itself. All of them enable parsing, searching, filtering, classification, summarization, and data unification with different trade-offs among labor, speed, and accuracy. We deploy this system to extract 26 257 distinct synthesis parameters pertaining to approximately 800 MOFs sourced from peer-reviewed research articles. This process incorporates our ChemPrompt Engineering strategy to instruct ChatGPT in text mining, resulting in impressive precision, recall, and F1 scores of 90–99%. Furthermore, with the data set built by text mining, we constructed a machine-learning model with over 87% accuracy in predicting MOF experimental crystallization outcomes and preliminarily identifying important factors in MOF crystallization. We also developed a reliable data-grounded MOF chatbot to answer questions about chemical reactions and synthesis procedures. Given that the process of using ChatGPT reliably mines and tabulates diverse MOF synthesis information in a unified format while using only narrative language requiring no coding expertise, we anticipate that our ChatGPT Chemistry Assistant will be very useful across various other chemistry subdisciplines.

Development of multivariate metal−organic frameworks (MOFs) as derivatives of the state-of-art water-harvesting material MOF-303 {[Al(OH)(PZDC)], where PZDC 2− is 1Hpyrazole-3,5-dicarboxylate} was shown to be a powerful tool to generate efficient water sorbents tailored to a given environmental condition. Herein, a new multivariate MOF-303-based waterharvesting framework series from readily available reactants is developed. The resulting MOFs exhibit a larger degree of tunability in the operational relative humidity range (16%), regeneration temperature (14 °C), and desorption enthalpy (5 kJ mol −1 ) than reported previously. Additionally, a high-yielding (≥90%) and scalable (∼3.5 kg) synthesis is demonstrated in water and with excellent space-time yields, without compromising framework crystallinity, porosity, and water-harvesting performance.

A linker extension strategy for generating metal− organic frameworks (MOFs) with superior moisture-capturing properties is presented. Applying this design approach involving experiment and computation results in MOF-LA2-1 {[Al(OH)-(PZVDC)], where PZVDC 2− is (E)-5-(2-carboxylatovinyl)-1Hpyrazole-3-carboxylate}, which exhibits an approximately 50% water capacity increase compared to the state-of-the-art water-harvesting material MOF-303. The power of this approach is the increase in pore volume while retaining the ability of the MOF to harvest water in arid environments under long-term uptake and release cycling, as well as affording a reduction in regeneration heat and temperature. Density functional theory calculations and Monte Carlo simulations give detailed insight pertaining to framework structure, water interactions within its pores, and the resulting water sorption isotherm.

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The synthetic scalability of water harvesting metal–organic frameworks (MOFs) is crucial for making these promising materials accessible and widely available for use in household devices. Herein, we present a facile, sustainable, and high-yield synthesis method to produce a series of water-harvesting MOFs, including MOF-303, CAU-23, MIL-160, MOF-313, CAU-10, and Al-fumarate. Using readily available reactants and water as the only solvent, we were able to synthesize these materials at the kilogram scale in a 200 L batch reactor with yields of 84–96% and space-time yields of 238–305 kg/day/m3 under optimized reaction conditions. We also show that our procedure preserves framework crystallinity, porosity, and water-harvesting performance of the MOFs synthesized at scale.

We report a new hydroxamate‐based yttrium MOF, named MOF‐419 [Y(HCOO)(BDH)], with rod‐SBUs. The compound was synthesized employing chelating construction of benzene‐1,4‐hydroxamate (BDH2−) linkers, and the use of formic acid as the modulator was found to be crucial for the formation of rod‐shaped SBUs. MOF‐419 shows permanent porosity and has a BET surface area of 1130 m2/g. Its hydrophobic pore environment and gas sorption properties were demonstrated through the combination of single crystal X‐ray diffraction and nitrogen, carbon dioxide, and water sorption experiments. We envision that these results will aid the study and understanding of rod MOFs with chelating linkages.

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