@Article{cmes.2020.010165,
AUTHOR = {Yi Yang, Robert Nawrocki, Richard Voyles, Haiyan H. Zhang},
TITLE = {Modeling of an Internal Stress and Strain Distribution of an Inverted Staggered Thin-Film Transistor Based on Two-Dimensional Mass-Spring-Damper Structure},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {125},
YEAR = {2020},
NUMBER = {2},
PAGES = {515--539},
URL = {http://www.techscience.com/CMES/v125n2/40307},
ISSN = {1526-1506},
ABSTRACT = {Equipped with a two-dimensional topological structure, a group
of masses, springs and dampers can be demonstrated to model the internal
dynamics of a thin-film transistor (TFT). In this paper, the two-dimensional
Mass-Spring-Damper (MSD) representation of an inverted staggered TFT
is proposed to explore the TFT’s internal stress/strain distributions, and the
stress-induced effects on TFT’s electrical characteristics. The 2D MSD model
is composed of a finite but massive number of interconnected cellular units.
The parameters, such as mass, stiffness, and damping ratios, of each cellular
unit are approximated from constitutive equations of the composite materials,
while the electrical properties of the inverted staggered TFT are characterized
by utilizing an electro-mechanical coupling relation derived from the quantum
mechanics. TFTs are often used in biomedical sensors/transducers attached to
human skins, and, for the purpose of simulation and validation, the boundary conditions on the interface between the TFT and the human skin were
modeled as a spatially distributed sinusoidal excitation with a frequency of
50 Hz, assuming the TFT thickness is more than tens of microns. The fidelity
of the 2D MSD structure in the modeling of an inverted staggered TFT is
verified by comparing its simulated total displacement field with that of a finite
element analysis (FEA) model. The advantages of the MSD model include
a dramatic reduction in memory use by up to 60% and faster computation
times that are up to 80% lower. More importantly, the MSD model is better
suited than FEA to many problems in accurate tissue modeling for medical
applications, for which FEA is becoming a bottleneck. This work develops a
novel modeling approach, which can be extended to other types of flexible
thin film transistors.},
DOI = {10.32604/cmes.2020.010165}
}