Applied and Computational Engineering,
Год журнала:
2025,
Номер
123(1), С. 119 - 133
Опубликована: Янв. 7, 2025
Decarbonization
and
development
of
clean
energy
has
long
been
a
challenge
require
the
reconstruction
consumption.
Hydrogen
emerges
as
promising
alternative
source
due
to
its
high
hear
capacity
negligible
carbon
emission.
However,
there
exist
lack
effective
efficient
approach
store,
transport,
recover
hydrogen
for
utilization.
Solid
materials
hold
promises
resolve
challenge.
Metal-organic
frameworks
(MOFs)
is
class
hybrid
organic
inorganic
that
exhibit
porosity
diverse
chemistry
rendering
them
suitable
gas
storage
separation.
Screening
optimal
MOFs
becomes
persistent
research
pursuit
infinite
number
MOF
materials.
Herein,
we
propose
computational
data-drive
throughput
screening
pipeline
storage.
We
generated
over
database
with
2000
prototypes
optimized
structures.
The
capacities
these
were
predicted
identification
top-performing
investigation
structure-property
relationships.
identify
top
candidates
superior
performance
than
reference
synthesizability.
relationship
between
metal
chemistry,
topology
revealed
future
experimental
guidance.
Nanomaterials,
Год журнала:
2025,
Номер
15(5), С. 336 - 336
Опубликована: Фев. 21, 2025
Iron-based
metal-organic
frameworks
(Fe-MOFs)
are
widely
used
for
agricultural
chemical
delivery
due
to
their
high
loading
capacity,
and
they
also
have
the
potential
provide
essential
iron
plant
growth.
Therefore,
hold
significant
promise
applications.
Evaluating
biotoxicity
of
Fe-MOFs
is
crucial
optimizing
use
in
agriculture.
In
this
study,
we
natural
biomacromolecule
carboxymethyl
cellulose
(CMC)
encapsulate
Fe-MOF
NH2-MIL-101
(Fe)
(MIL).
Through
hydroponic
experiments,
investigated
biotoxic
effects
on
rice
before
after
CMC
modification.
The
results
show
that
accumulation
dependent
dose
exposure
concentration
Fe-MOFs.
modification
(MIL@CMC)
can
reduce
release
rate
Fe
ions
from
aqueous
solutions
with
different
pH
values
(5
7).
Furthermore,
MIL@CMC
treatment
significantly
increases
absorption
by
both
aboveground
root
parts
rice.
alleviated
growth
inhibition
seedlings
increased
biomass
under
medium-
high-exposure
conditions.
Specifically,
roots,
MIL
induced
a
more
intense
oxidative
stress
response,
activities
related
antioxidant
enzymes
(CAT,
POD,
SOD)
MDA
content.
Our
demonstrated
encapsulation
NH2-MIL-101(Fe)
using
effectively
damage
promoted
uptake
These
findings
suggest
rational
positive
effect
reducing
phytotoxicity
MOFs
improving
biosafety
Journal of Materials Chemistry A,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 1, 2025
Metal-organic
frameworks
(MOFs)
are
porous,
crystalline
materials
with
high
surface
area,
adjustable
porosity,
and
structural
tunability,
making
them
ideal
for
diverse
applications.
However,
traditional
experimental
computational
methods
have
limited
scalability
interpretability,
hindering
effective
exploration
of
MOF
structure-property
relationships.
To
address
these
challenges,
we
introduce,
the
first
time,
a
category-specific
topological
learning
(CSTL),
which
combines
algebraic
topology
chemical
insights
robust
property
prediction.
The
model
represents
structures
as
simplicial
complexes
incorporates
elemental
categorizations
to
enable
balanced,
interpretable
machine
study.
By
integrating
persistent
homology,
CSTL
captures
both
global
local
characteristics,
rendering
multi-dimensional,
descriptors
that
support
predictive
accuracy
robustness
across
eight
datasets,
outperforming
all
previous
results.
This
alignment
features
enhances
power
interpretability
CSTL,
advancing
understanding
relationships
MOFs
promoting
efficient
material
discovery.
Molecules,
Год журнала:
2024,
Номер
29(15), С. 3512 - 3512
Опубликована: Июль 26, 2024
The
rational
design,
activity
prediction,
and
adaptive
application
of
biological
elements
(bio-elements)
are
crucial
research
fields
in
synthetic
biology.
Currently,
a
major
challenge
the
field
is
efficiently
designing
desired
bio-elements
accurately
predicting
their
using
vast
datasets.
advancement
artificial
intelligence
(AI)
technology
has
enabled
machine
learning
deep
algorithms
to
excel
uncovering
patterns
bio-element
data
performance.
This
review
explores
AI
design
bio-elements,
regulation
transcription-factor-based
biosensor
response
performance
AI-designed
elements.
We
discuss
advantages,
adaptability,
challenges
addressed
by
various
applications,
highlighting
powerful
potential
analyzing
data.
Furthermore,
we
propose
innovative
solutions
faced
suggest
future
directions.
By
consolidating
current
demonstrating
practical
applications
biology,
this
provides
valuable
insights
for
advancing
both
academic
biotechnology.
Applied and Computational Engineering,
Год журнала:
2025,
Номер
123(1), С. 119 - 133
Опубликована: Янв. 7, 2025
Decarbonization
and
development
of
clean
energy
has
long
been
a
challenge
require
the
reconstruction
consumption.
Hydrogen
emerges
as
promising
alternative
source
due
to
its
high
hear
capacity
negligible
carbon
emission.
However,
there
exist
lack
effective
efficient
approach
store,
transport,
recover
hydrogen
for
utilization.
Solid
materials
hold
promises
resolve
challenge.
Metal-organic
frameworks
(MOFs)
is
class
hybrid
organic
inorganic
that
exhibit
porosity
diverse
chemistry
rendering
them
suitable
gas
storage
separation.
Screening
optimal
MOFs
becomes
persistent
research
pursuit
infinite
number
MOF
materials.
Herein,
we
propose
computational
data-drive
throughput
screening
pipeline
storage.
We
generated
over
database
with
2000
prototypes
optimized
structures.
The
capacities
these
were
predicted
identification
top-performing
investigation
structure-property
relationships.
identify
top
candidates
superior
performance
than
reference
synthesizability.
relationship
between
metal
chemistry,
topology
revealed
future
experimental
guidance.
