What is it about?
Finding new chemicals for applications is very costly computationally as well as synthetically/experimentally. This process can be accelerated with better optimization methods. In this case, the application problem are better chemicals for electro-optics such as OLEDs found in modern flat-screen televisions.
Featured Image
Why is it important?
The optimization method, which can be connected to other algorithm classes, is shown to be fast and produces some nontrivial solutions that human intuition would not come up with.
Perspectives
Many chemists focus on stochastic optimization methods such as genetic algorithms, which do not have hard convergence criteria or guarantees. Deterministic optimizations do have these criteria and guarantees and tend to converge very quickly. When hybrid approaches will become more prevalent as they have in other areas, then the question of which deterministic methods should be considered will arise. The algorithm presented here due to its simplicity shows the path of what types of algorithms should be considered.
Dr Berend C Rinderspacher
US ARL
Read the Original
This page is a summary of: Discrete Optimization of Electronic Hyperpolarizabilities in a Chemical Subspace, Journal of Chemical Theory and Computation, December 2009, American Chemical Society (ACS),
DOI: 10.1021/ct900325p.
You can read the full text:
Contributors
The following have contributed to this page
