Text mining of synthesis methods of metal organic framework
Project Description

The past decade has experienced the explosive growth in the study of materials known as metal-organic frameworks (MOFs), which is one of the extensive classes of crystalline materials that have ultra-high porosity and huge internal surface areas ( porosity up to 90% free volume, surface extending over 6000 m2/g). These materials are constituted by joining molecular building blocks such as metal cluster with the organic linker, with high degrees of variability for both organic and inorganic components result in thousands of compounds being synthesized and studied every year. These outstanding properties, together with high variety make MOFs have potential for numerous application such as gas storage and separation, charge transport and storage, drug delivery.

Supervisor
SU Haibin
Quota
1
Course type
UROP1000
UROP1100
UROP2100
UROP3100
UROP4100
Applicant's Roles

using text mining to design a computer-based expert system for searching application-specific MOFs from collated publications database and proposing correspondingly useful synthesis methods.

Applicant's Learning Objectives

training in text mining, research experiences in MOF materials

Complexity of the project
Challenging