Software predicts battery failure
Article Abstract:
A neural-network pattern-recognition software for predicting the performance, deterioration and failure of long-life rechargeable batteries has been developed by researchers at Pennsylvania State University. The researchers used the neural network, with battery data supplied by NASA, in determining the future performance of the batteries including operational temperature, current/time signatures imposed on the batteries, output voltage and time of battery failure.
Publication Name: Chemical Engineering Progress
Subject: Engineering and manufacturing industries
ISSN: 0360-7275
Year: 1998
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Single-Walled carbon nanotubes strike gold, silver sand copper
Article Abstract:
The successful research conducted by Tokyo University for developing high quality single-walled carbon nanotubes by using various metals is discussed.
Publication Name: Chemical Engineering Progress
Subject: Engineering and manufacturing industries
ISSN: 0360-7275
Year: 2007
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Nanopolymers: discovering a new class of materials
Article Abstract:
The details of the nanopolymers that are useful in creating new materials, developed by Massachusetts Institute of Technology, are presented.
Publication Name: Chemical Engineering Progress
Subject: Engineering and manufacturing industries
ISSN: 0360-7275
Year: 2007
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