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The chemical flexibility of metal-organic frameworks (MOFs) offers an ideal platform to tune structure and composition for specific applications, from gas sensing to catalysis and from photoelectric conversion to energy storage. This…
Metal-organic frameworks (MOFs) are an attractive substrate for catalytic reactions due to the high area density of reaction sites and the ability to tailor an array of material attributes. This study focuses on a thermally stable…
We develop a computational workflow for high-throughput Wannierization of density functional theory (DFT) based electronic band structure calculations. We apply this workflow to 1771 materials, and we create a database with the resulting…
Metal organic frameworks (MOFs) are promising photocatalytic materials due to their high surface area and tuneability of their electronic structure. We discuss here how to engineer the band structures and optical properties of a family of…
Long-lived emissive materials based on room temperature phosphorescence (RTP) and thermally activated delayed fluorescence (TADF) are considered as the cornerstone of the development of optical sensors, security systems and solid-state…
Coordination polymerization leads to various metal-organic frameworks (MOFs) in which symmetrical metal nodes exposed to nano voids lead to unique physical properties and chemical functionalities. One of the challenges towards their…
Recently, metal-organic frameworks (MOFs) have demonstrated their potential as solid-state electrolytes in proton exchange membrane fuel cells. However, the number of MOFs reported to exhibit proton conductivity remains limited, and the…
Magnetic metal-organic frameworks (MMOFs), where magnetic metal nodes are connected into a crystal structure by organic linkers, have a potential to host exotic magnetic states. We present a study of bulk magnetic properties of four…
By virtue of their open network structures and low densities, metal--organic frameworks (MOFs) are soft materials that exhibit elastic instabilities at low applied stresses. The conventional strategy for improving elastic stability is to…
We report a molecular-dynamics simulation of a single-component system of particles interacting via a spherically symmetric potential that is found to form, upon cooling from a liquid state, a low-density porous crystalline phase. Its…
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…
DFT+U is a widely used treatment in the density functional theory (DFT) to deal with correlated materials that contain open-shell elements, whereby the quantitative and sometimes even qualitative failures of local and semilocal…
Metal-insulator transition (MIT) materials are a useful platform for emerging microelectronic, optoelectronic, and neuromorphic devices, but their discovery is hindered by the high computational cost of electronic structure modeling, the…
Molecular dynamics simulations combined with periodic electronic structure calculations are performed to decipher structural, thermodynamical and dynamical properties of the interfaced vs. confined water adsorbed in hexagonal 1D channels of…
An in-depth insight into the chemistry and nature of the individual chemical bonds is essential for understanding materials. Bonding analysis is thus expected to provide important features for large-scale data analysis and machine learning…
Metal-organic frameworks (MOFs) are highly interesting and tunable materials. By incorporating spatial defects into their atomic structure, MOFs can be finetuned to exhibit precise chemical functionalities, extending their applicability in…
Carbon capture is vital for decarbonizing heavy industries such as steel and chemicals. Metal-organic frameworks (MOFs), with their high surface area and structural tunability, are promising materials for CO2 capture. This study focuses on…
We present a high-accuracy procedure for electronic structure calculations of strongly correlated materials. To address limitations in current electronic structure methods, we employ density functional theory in combination with the…
Conventionally, high-throughput computational materials searches start from an input set of bulk compounds extracted from material databases, and this set is screened for candidate materials for specific applications. In contrast, many…
The removal of leaked radioactive iodine isotopes in humid environments holds significant importance in nuclear waste management and nuclear accident mitigation. In this study, high-throughput computational screening and machine learning…