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Dynamic thermal model development of direct methanol fuel cell
Mohammad Biswas, Tabbi Wilberforce
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Corresponding author for this work
Mechanical, Biomedical & Design Engineering
College of Engineering and Physical Sciences
Research output
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Article
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peer-review
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Dive into the research topics of 'Dynamic thermal model development of direct methanol fuel cell'. Together they form a unique fingerprint.
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Engineering & Materials Science
Direct methanol fuel cells (DMFC)
100%
Neural networks
36%
Hot Temperature
35%
Methanol
30%
Cathodes
29%
Anodes
28%
Inlet flow
18%
Byproducts
15%
Carbon dioxide
13%
Mean square error
13%
Neurons
13%
Learning algorithms
12%
Flow rate
11%
Liquids
9%
Air
8%
Water
8%
Temperature
5%
Physics & Astronomy
fuel cells
86%
methyl alcohol
76%
anodes
18%
cathodes
17%
inlet flow
15%
optimal control
13%
learning
11%
predictions
11%
carbon dioxide
10%
neurons
10%
performance
9%
flow velocity
8%
air
6%
water
6%
coefficients
5%
cells
5%
liquids
5%
temperature
3%
Chemistry
Anode
21%
Cathode
21%
Methanol
18%
Carbon Dioxide
11%
Flow Kinetics
11%
Error
11%
Environment
8%
Liquid
8%
Application
4%