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In Silico Design of 2D and 3D Covalent Organic Frameworks for Methane Storage...
Here we present 69,840 covalent organic frameworks (COFs) assembled in silico from a set of 666 distinct organic linkers into 2D-layered and 3D configurations. We investigate... -
In Silico Design of 2D and 3D Covalent Organic Frameworks for Methane Storage...
Here we present 69,840 covalent organic frameworks (COFs) assembled in silico from a set of 666 distinct organic linkers into 2D-layered and 3D configurations. We investigate... -
In Silico Design of 2D and 3D Covalent Organic Frameworks for Methane Storage...
Here we present 69,840 covalent organic frameworks (COFs) assembled in silico from a set of 666 distinct organic linkers into 2D-layered and 3D configurations. We investigate... -
The Influence of Intrinsic Framework Flexibility on Adsorption in Nanoporous ...
Project Abstract: For applications of metal-organic frameworks (MOFs) such as gas storage and separation, flexibility is often seen as a parameter that can tune material... -
The Influence of Intrinsic Framework Flexibility on Adsorption in Nanoporous ...
Project Abstract: For applications of metal-organic frameworks (MOFs) such as gas storage and separation, flexibility is often seen as a parameter that can tune material... -
In silico design of three-dimensional porous covalent organic frameworks via ...
Covalent organic frameworks (COFs) are a class of advanced nanoporous polymeric materials which combine the crystallinity of metal–organic frameworks (MOFs) with the stability... -
Capturing chemical intuition in synthesis of metal-organic frameworks
We report a methodology using machine learning to capture chemical intuition from a set of (partially) failed attempts to synthesize a metal organic framework. We define... -
Capturing chemical intuition in synthesis of metal-organic frameworks
We report a methodology using machine learning to capture chemical intuition from a set of (partially) failed attempts to synthesize a metal organic framework. We define... -
Capturing chemical intuition in synthesis of metal-organic frameworks
We report a methodology using machine learning to capture chemical intuition from a set of (partially) failed attempts to synthesize a metal organic framework. We define... -
Synthesis of Metal-Organic Frameworks: capturing chemical intuition
We report a methodology using machine learning to capture chemical intuition from a set of (partially) failed attempts to synthesize a metal organic framework. We define... -
In Silico Design of Porous Polymer Networks: High Throughput Screening for Me...
Porous polymer networks (PPNs) are a class of advanced porous materials that combine the advantages of cheap and stable polymers with the high surface areas and tunable... -
Mail-order metal-organic frameworks (MOFs): designing isoreticular MOF-5 anal...
Metal–organic frameworks (MOFs), a class of porous materials, are of particular interest in gas storage and separation applications due largely to their high internal surface... -
Mail-order metal-organic frameworks (MOFs): designing isoreticular MOF-5 anal...
Metal–organic frameworks (MOFs), a class of porous materials, are of particular interest in gas storage and separation applications due largely to their high internal surface... -
Accurate Characterization of the Pore Volume in Microporous Crystalline Mater...
Project Abstract: Pore volume is one of the main properties for the characterization of microporous crystals. It is experimentally measurable and it can also be obtained from...
