Cited Article: Holt JK. Fast mass transport through sub-2-nanometer carbon nanotubes
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AU Ahadian, S
Kawazoe, Y
AF Ahadian, Samad
Kawazoe, Yoshiyuki
TI An Artificial Intelligence Approach for Modeling and Prediction of
Water Diffusion Inside a Carbon Nanotube
SO NANOSCALE RESEARCH LETTERS
LA English
DT Article
DE Carbon nanotube; Water diffusion; Artificial intelligence; Modeling and
prediction
ID FAST MASS-TRANSPORT; PERMEATION; CHANNELS; BEHAVIOR
AB Modeling of water flow in carbon nanotubes is still a challenge for the
classic models of fluid dynamics. In this investigation, an
adaptive-network-based fuzzy inference system (ANFIS) is presented to
solve this problem. The proposed ANFIS approach can construct an
input-output mapping based on both human knowledge in the form of fuzzy
if-then rules and stipulated input-output data pairs. Good performance
of the designed ANFIS ensures its capability as a promising tool for
modeling and prediction of fluid flow at nanoscale where the continuum
models of fluid dynamics tend to break down.
C1 [Ahadian, Samad; Kawazoe, Yoshiyuki] Tohoku Univ, Inst Mat Res, Sendai, Miyagi 9808577, Japan.
RP Ahadian, S, Tohoku Univ, Inst Mat Res, Sendai, Miyagi 9808577, Japan.
EM ahadian@imr.edu
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NR 25
TC 0
PU SPRINGER; 233 SPRING ST, NEW YORK, NY 10013 USA
SN 1931-7573
DI 10.1007/s11671-009-9361-3
PD SEP
VL 4
IS 9
BP 1054
EP 1058
SC Nanoscience & Nanotechnology; Materials Science, Multidisciplinary;
Physics, Applied
GA 483ZU
UT ISI:000269013100014
ER
PT J
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AF Tabeling, P.
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systems
SO LAB ON A CHIP
LA English
DT Review
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MASS-TRANSPORT; BOUNDARY SLIP; LONG BUBBLES; FLOW; MICROCHANNELS;
WATER; MICROMIXERS
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NR 105
TC 0
PU ROYAL SOC CHEMISTRY; THOMAS GRAHAM HOUSE, SCIENCE PARK, MILTON RD,
CAMBRIDGE CB4 0WF, CAMBS,
ENGLAND
SN 1473-0197
DI 10.1039/b904937c
VL 9
IS 17
BP 2428
EP 2436
SC Biochemical Research Methods; Chemistry, Multidisciplinary; Nanoscience
& Nanotechnology
GA 483NZ
UT ISI:000268975200002
ER
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