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Metal-Organic Frameworks (MOFs) are materials with a high degree of porosity that can be used for applications in energy storage, water desalination, gas storage, and gas separation. However, the chemical space of MOFs is close to an…
Metal-organic frameworks (MOFs) are a class of crystalline materials with promising applications in many areas such as carbon capture and drug delivery. In this work, we introduce MOFFlow, the first deep generative model tailored for MOF…
Metal-organic frameworks (MOFs) are promising materials for methane capture due to their high surface area and tunable properties. Metal substitution represents a powerful strategy to enhance MOF performance, yet systematic exploration of…
Metal-organic frameworks (MOFs) are an incredibly diverse group of highly porous hybrid materials, which are interesting for a wide range of possible applications. For a reliable description of many of their properties accurate…
Metal-organic frameworks (MOFs) symbolize the particular class of hybrid crystalline, nano-porous materials made of either discrete metal ions or clusters with organic linkers. Past studies on MOFs-based materials largely focused on…
Due the alarming rate of climate change, the implementation of efficient CO$_2$ capture has become crucial. This project aims to create an algorithm that predicts the uptake of CO$_2$ adsorbing Metal-Organic Frameworks (MOFs) by using…
Metal-organic frameworks (MOFs) have been widely investigated for challenging catalytic transformations due to their well-defined structures and high degree of synthetic tunability. These features, at least in principle, make MOFs ideally…
The enormous structural and chemical diversity of metal-organic frameworks (MOFs) forces researchers to actively use simulation techniques on an equal footing with experiments. MOFs are widely known for outstanding adsorption properties, so…
Metal-organic frameworks (MOFs) are a specific class of hybrid, crystalline, nano-porous materials made of metal-ion-based nodes and organic linkers. Most of the studies on MOFs largely focused on porosity, chemical and structural…
Although the tailored metal active sites and porous architectures of MOFs hold great promise for engineering challenges ranging from gas separations to catalysis, a lack of understanding of how to improve their stability limits their use in…
Identifying optimal synthesis conditions for metal-organic frameworks (MOFs) is a major challenge that can serve as a bottleneck for new materials discovery and development. Trial-and-error approach that relies on a chemist's intuition and…
Metal-organic frameworks (MOFs) are a family of materials that have high porosity and structural tunability and hold great potential in various applications, many of which requiring a proper understanding of the thermal transport…
Over the past decade, climate change has become an increasing problem with one of the major contributing factors being carbon dioxide (CO2) emissions; almost 51% of total US carbon emissions are from factories. Current materials used in CO2…
Metal-organic frameworks (MOFs) have emerged as promising materials for various applications due to their unique structural properties and versatile functionalities. This study presents a comprehensive investigation of machine learning…
Recently, machine-learning approaches have accelerated computational materials design and the search for advanced solid electrolytes. However, the predictors are currently limited to static structural parameters, which may not fully account…
Understanding how structural flexibility affects the properties of metal-organic frameworks (MOFs) is crucial for the design of better MOFs for targeted applications. Flexible MOFs can be studied with molecular dynamics simulations, whose…
Metal-organic frameworks (MOFs) provide a versatile and tailorable material platform that embody many desirable attributes for photocatalytic water-splitting. The approach taken in this study was to use Density Functional Theory (DFT) to…
The thermal conductivity of organic liquids is a vital parameter influencing various industrial and environmental applications, including energy conversion, electronics cooling, and chemical processing. However, atomistic simulation of…
High-throughput screening of large hypothetical databases of metal-organic frameworks (MOFs) can uncover new materials, but their stability in real-world applications is often unknown. We leverage community knowledge and machine learning…
This research was focused on the efficient collection of experimental Metal-Organic Framework (MOF) data from scientific literature to address the challenges of accessing hard-to-find data and improving the quality of information available…