Atomic Property Weighted Radial Distribution Functions Descriptors of Metal–Organic Frameworks for the Prediction of Gas Uptake Capacity

By Michael Fernández, Nicholas R. Trefiak, Tom K. Woo. 2013

140 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/ffbe0e8084c88ff11b25615f6a8281a5b7a42ce4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Xu Zhang
2. An Chen
3. Zhen Zhou

Citations in the corpus

• Big Data Creates New Opportunities for Materials Research: A Review on Methods and Applications of Machine Learning for Materials Design (2019, unknown): “The RDF, which is usually denoted by g ( r ), defines the probability of finding a particle or atom at a distance r from another tagged particle or atom [38].”
• Machine learning: Accelerating materials development for energy storage and conversion (2020, methodology): “The gas adsorption capacity, including methane, N2 and CO2, has been investigated.(83,193,194) Atomic property weighted radial distribution function (AP-RDF) was introduced to capture the chemical and geometric features.”