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Computational modeling of molecularly imprinted polymers as a green approach to the development of novel analytical sorbents
- Source :
- Trac-Trends in Analytical Chemistry. 98:64-78
- Publication Year :
- 2018
-
Abstract
- The development of novel molecularly imprinted polymers (MIP) sorbents for specific chemical compounds require a lot of tedious and time-consuming laboratory work. Significant quantities of solvents and reagents are consumed in the course of the verification of appropriate configurations of polymerization reagents. Implementation of molecular modeling in the MIP sorbent development process appears to provide a solution to this problem. Appropriate simulations and computations facilitate the determination of the nature of interaction between the reagents and thus the selection of the best configuration of chemicals for the preparation of the sorbent. The article presents literature information on major computer software used for molecular modeling, its application in the development of MIP sorbents, as well as the advantages resulting from the implementation of computer-assisted techniques. The appropriate choice of polymerization reagents and conditions allows for a significant reduction of the adverse environmental impact of the entire laboratory process.
- Subjects :
- computational modeling
Sorbent
business.industry
Computer science
010401 analytical chemistry
Molecularly imprinted polymer
green analytical sorbents
02 engineering and technology
basic laboratory studies
021001 nanoscience & nanotechnology
01 natural sciences
0104 chemical sciences
Analytical Chemistry
green analytical chemistry
Polymerization
Computer software
Organic chemistry
molecularly imprinted polymers
0210 nano-technology
Process engineering
business
Spectroscopy
Subjects
Details
- Language :
- English
- ISSN :
- 01659936
- Volume :
- 98
- Database :
- OpenAIRE
- Journal :
- Trac-Trends in Analytical Chemistry
- Accession number :
- edsair.doi.dedup.....bb521b54381a785c5f6bf881006e63f1
- Full Text :
- https://doi.org/10.1016/j.trac.2017.10.020