The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON COMPUTERS
Transactions ID Number: 54-169
Full Name: Hugh Cartwright
Position: Lecturer
Age: ON
Sex: Male
Address: Chemistry Department, PTCL, Oxford University, South Parks Road, Oxford OX1 3QZ
Country: UNITED KINGDOM
Tel: 1865275483
Tel prefix: 44
Fax:
E-mail address: Hugh.Cartwright@chem.ox.ac.uk
Other E-mails:
Title of the Paper: Use of a Genetic Algorithm-Neural Network hybrid algorithm in the search for high efficiency solid-state phosphors
Authors as they appear in the Paper: Hugh Cartwright and Arsenij Leontjev
Email addresses of all the authors: Hugh.Cartwright@chem.ox.ac.uk
Number of paper pages: 10
Abstract: Artificial Intelligence methods have been employed in the search for solid-state phosphors with a high luminescence quantum yield. An Artificial Neural Network was used to investigate how luminescence efficiency can be linked to phosphor composition. The trained network was then coupled to a Genetic Algorithm whose role was to locate the global optimum composition in the search space. The compound Tb0.039Gd0.104Ce0.063Si0.401B0.393Ox (where x indicates the stoichiometrically-required amount of oxygen) is estimated to be the optimum oxide composition that generates the highest green phosphor luminescence for use in tricolour white LEDs, when excited by a 400 nm light source.
Keywords: Genetic Algorithm, Artificial Neural Network, phosphor, LED, oxide, hybrid algorithm.
EXTENSION of the file: .pdf
Special (Invited) Session: Applied Soft Computing
Organizer of the Session: Prof Les Sztandera
How Did you learn about congress: Artificial Intelligence, Genetic Algorithms, Neural Network, solid-state chemistry, light-emitting diodes
IP ADDRESS: 129.67.105.150
