May 19, 2023 · Herein, we report two highly crystalline 3D COFs with pto and mhq-z topologies designed by rationally selecting rectangular-planar and trigonal-planar building blocks with appropriate...

Jan 26, 2024 · Our research uncovers a new topology in COFs and reveals structural insights into the reticular design of high-efficiency sorbents of iodine.

Apr 4, 2022 · Integrating the unique kgd topology with small rhombic micropores, these 2D COFs are endowed with both short molecular diffusion length and favorable host–guest interaction, exhibiting potential for drug delivery with high loading and good release control of ibuprofen.

Dec 17, 2020 · Here we report a 3D-COF with the ceq topology utilizing a D3h -symmetric triangular prism vertex with a planar triangular linker. The as-synthesized COF displays a twofold-interpenetrated structure with a Brunauer–Emmett–Teller surface area of 1148.6 m 2 g –1.

Jun 1, 2021 · Several approaches have been developed to construct COFs with diverse topologies from various building units. COFs could be used in gas adsorption, catalysis, and energy storage. COFs could be used to improve the charge carrier transport and photoconductive properties of photovoltaic cells.

Sep 8, 2020 · Covalent organic frameworks (COFs) represent a novel type of crystalline porous polymers with potential applications in many areas. Considering their covalent connectivity in different dimensions, COFs are classified as two-dimensional (2D) layered structures or three-dimensional (3D) networks.

Apr 1, 2024 · High valency and functionalization are two key strategies of 3D COFs design, including the development of building blocks, topology, linkage and post synthetic modification strategy.

Covalent organic frameworks (COFs) are two- or three-dimensional (2D, 3D) families of materials, which, through interactions between organic precursors, produce strong, covalent networks that enable the formation of porous, constant, and crystalline solids [1, 2].

Topospace specializes in AI-driven reticular chemistry, enhancing MOFs, COFs, and HOFs. Our innovative models predict structures and performance, ensuring optimal post-modification outcomes for advanced material applications.

At Topospace, we leverage AI to enhance reticular chemistry, focusing on MOFs, COFs, and HOFs for structure and performance predictions. We specialize in intelligent predictions and modifications, exemplified by our CU-MOF node type prediction and DeepSeek-R1-driven MOF post-modification models.