Foresight Nanotech Institute Logo
Image of nano


Computational neural networks:
a general purpose tool
for nanotechnology

S.A. Meyer*(a), M. Morgenstern(a), J.A. Darsey(b),
D.W. Noid(c), B.G. Sumpter(c)

          (a)Department of Chemistry, Colorado State College
(b) Department of Chemistry, University of Arkansas, Little Rock
(c) Oak Ridge National Laboratory
email:
smeyer@cc.colorado.edu

This is an abstract for a poster to be presented at the
Fifth Foresight Conference on Molecular Nanotechnology.
There will be a link from here to the full article when it is available on the web.

 

A computational scheme which utilizes neural networks was developed to predict properties of nano-structured materials and optimization and control of nano-devices. Using a set of simple algorithms to encode the structure and composition of the material directly into numerical vectors neural network modules can correlate these numeric inputs with a set of desired properties. Calculated results for a series of hydrocarbons, fluorohydrocarbons, amines, and crown ethers demonstrate average accuracies of 0.2-8.1% with maximum deviations of 16-20% for a broad range of thermodynamic, physical, biological (toxicity: human and environmental) and physical-chemical characteristics (heat capacity, enthalpy, heat of evaporation, boiling point, density, refractive index, stability constants, etc.). A molecular design tool based on the neural network capabilities of formulating accurate quantitative structure-property relationships is described. This technique, called computational synthesis, is capable of formulating the structure and composition of materials which will give a set of specified properties. In other applications, this technique has been proven useful in the reverse engineering of nano-fluidics and nano-motors.

Research sponsored by the Division of Materials Sciences, Office of Basic Energy Sciences, U.S. Department of Energy under contract DE-AC05-96OR22464 with Lockheed-Martin Energy Research Corp.


*Corresponding Address:
Sally A. Meyer, Oak Ridge National Laboratory, Chemical and Analytical Sciences Division
P. O. Box 2008, Oak Ridge, TN 37831-6197
ph: (423) 574-4974, fax: (423) 576-5235, email: smeyer@cc.colorado.edu



Donate Now

 

Foresight Programs

Join Now

 

Home About Foresight Blog News & Events Roadmap About Nanotechnology Resources Facebook Contact Privacy Policy

Foresight materials on the Web are ©1986–2014 Foresight Institute. All rights reserved. Legal Notices.

Web site development by Netconcepts. Email marketing by gravityMail. Maintained by James B. Lewis Enterprises.