Mechanics of Materials,
Год журнала:
2024,
Номер
195, С. 105031 - 105031
Опубликована: Май 13, 2024
Soft
robots
and
sensor/actuator
systems
are
often
based
on
bioinspired
designs
to
leverage
nature
patterns.
Specifically,
pillar-shaped
sensors
useful
for
human
activity
monitoring,
locomotion
of
soft
or
treatment
cardiovascular
diseases.
If
electric
magnetic
particles
added
in
the
manufacturing
process,
these
structures
can
be
tuned
through
remote
fields
attain
a
specific
mechanical
behaviour.
This
promising
technique
has
direct
applications
high-impact
such
as
bioengineering,
sensor
designing.
Filament-shaped
smart
send
electrical
signals
when
subjected
an
external
stimulus
provide
response
controllable
field
is
applied
broadening
their
possibilities
action.
As
efficient
design
highly
challenging,
developing
technical
tool
with
low
computational
cost
help
throughout
layout
processes
(i.e.
inverse
engineering)
pivotal.
Theoretical
modelling
kinematics
dynamics
wire-shaped
structure
under
action
first
step
methodology
designing
efficient,
understandable
time-consuming
way.
The
event
deformation
after
receiving
before
sending
corresponding
output
signal
key
conceptualisation
process
sensors.
work
intends
give
insight
into
deformable
component
without
addressing
coupling
its
causes
and,
hence,
general
framework
serve
basis
multiphysics
formulations
design.
Journal of the Mechanics and Physics of Solids,
Год журнала:
2024,
Номер
192, С. 105791 - 105791
Опубликована: Июль 22, 2024
Magneto-active
hydrogels
(MAHs)
consist
of
a
polymeric
network
doped
with
magnetic
particles
that
enable
the
material
to
mechanically
respond
stimuli.
This
multifunctionality
allows
for
modulation
mechanical
properties
in
remote
and
dynamic
manner.
These
characteristics
combined
biocompatibility
hydrogels,
make
MAHs
excellent
drug
delivery
biological
scaffolds.
In
this
work,
ultra-soft
strong
magnetostriction
are
fabricated
from
human
blood
plasma
(∼20
Pa).
The
is
experimentally
tested
using
novel
in-house
device
precise
control
actuation
conditions,
enabling
hydrogel
terms
deformation
stiffness.
We
study
impact
on
solvent
expulsion
diffusion
dynamics
within
network.
To
further
elucidate
mechanisms
driving
processes,
computational
framework
modeling
process
two
different
species
magneto-responsive
proposed.
experimental
outcomes
open
exciting
new
opportunities
use
bioengineering
applications.
npj Computational Materials,
Год журнала:
2023,
Номер
9(1)
Опубликована: Июль 31, 2023
Abstract
Additive
manufacturing
has
enabled
the
design
of
thermoplastic
components
that
provide
structural
support,
electrical
conductivity
and
heat
generation
modulated
by
mechanical
deformation.
The
mechanisms
interplays
govern
material
response
at
microstructural
level
remain,
however,
elusive.
Here,
we
develop
an
experimental
method
to
characterise
conductive
filaments
from
a
combined
mechanical,
thermal
perspective.
This
approach
is
used
unravel
exciting
polylactic
acid.
To
overcome
limitations
prevent
complete
analysis
problem,
full-field
homogenisation
framework
implement
it
for
finite
elements.
accounts
viscoplasticity,
conduction,
convection
via
Joule
effect,
as
well
interdependences
between
them.
After
validation,
applied
virtually
optimise
fabrication
requirements
obtain
desired
properties
in
final
products,
i.e.,
stiffer
with
higher
conductivities
or
better
sensing
capabilities.
Computer Methods in Applied Mechanics and Engineering,
Год журнала:
2023,
Номер
415, С. 116211 - 116211
Опубликована: Июль 19, 2023
Soft
materials
such
as
biological
tissues
or
magnetorheological
elastomers
present
complex
mechanical
behaviors
that
include
large
deformations,
numerous
nonlinearities,
time-
even
external
field
(magnetic)-dependent
responses.
The
description
of
their
constitutive
modeling
is
challenging
and
often
time-consuming.
Numerical
algorithms
to
automatically
calibrate
model
parameters
have
provided
invaluable
tools
help
this
purpose.
However,
these
are
mostly
limited
the
fitting
a
set
pre-defined
associated
with
used.
In
work,
we
go
step
further
by
developing
machine
learning
framework
capable
identifying
not
only
but
also
optimal
kinematics
rheological
model.
To
end,
multiphysics
model-driven
optimally
selects
most
suitable
kinematics,
its
components
arrangement
for
given
experimental
curves.
Subsequently,
it
calibrates
all
material
constants
belonging
model,
independent
complexity.
We
demonstrate
versatility
capabilities
examples
on
hyperelastic,
viscohyperelastic
magneto-viscohyperelastic
materials.
work
opens
new
routes
fit
identify
ingredients
underlying
mechanisms
needed
describe
nonlinear
responses
soft
active
