Polycyclic aromatic compounds,
Год журнала:
2023,
Номер
unknown, С. 1 - 28
Опубликована: Дек. 12, 2023
Energy-efficient
non-fullerene
acceptors
attracting
great
attention
for
developing
efficient
organic
solar
cells
(OSCs).
Though
many
materials
have
been
developed
to
improve
the
optical
and
optoelectronic
characteristics
of
OSCs,
search
continues
strengthen
this
field
further.
Therefore,
herein,
we
designed
an
environmentally-benign
indacenodifuran-based
electron
acceptor
molecules
(MH1-MH8)
by
substituting
various
end-capped
electron-withdrawing
moieties
(COOH,
SO3H,
NO2,
CN).
The
open-circuit-voltages,
binding
energy,
transition
density
analysis,
hole
reorganization
energies
MH1–MH8
were
computed
these
materials.
These
MH1-MH8
better
photovoltaic,
photophysical,
electrical
properties
than
R
due
their
narrower
bandgap
(1.91
eV),
higher
absorption
(725.56
785.46
nm
in
gas
chloroform),
low-mobility
electrons
(0.0033)
holes
(0.0019),
lower
energy
0.20
eV).
We
also
performed
a
charge
transfer
study
establishing
donor:acceptor
complex
MH2:PTB7-TH,
showing
transformation
at
interface.
Thus,
compounds
with
excellent
could
be
considered
promising
environmentally
friendly
option
create
compelling
cells.
ACS Omega,
Год журнала:
2022,
Номер
7(51), С. 48139 - 48149
Опубликована: Дек. 13, 2022
Designing
molecules
for
drugs
has
been
a
hot
topic
many
decades.
However,
it
is
hard
and
expensive
to
find
new
molecule.
Thus,
the
cost
of
final
drug
also
increased.
Machine
learning
can
provide
fastest
way
predict
biological
activity
druglike
molecules.
In
present
work,
machine
models
are
trained
prediction
aromatase
inhibitors.
Data
was
collected
from
literature.
Molecular
descriptors
calculated
be
used
as
independent
features
model
training.
The
results
showed
that
R2
values
linear
regression,
random
forest
gradient
boosting
bagging
regression
0.58,
0.84,
0.77,
0.80,
respectively.
Using
these
models,
possible
in
short
period
time
at
reasonable
cost.
Furthermore,
Tanimoto
similarity
analysis,
well
chemical
database
mined
search
similar
Nonetheless,
this
study
provides
framework
repurposing
other
effective
prevent
cancer.
Journal of Saudi Chemical Society,
Год журнала:
2023,
Номер
27(4), С. 101670 - 101670
Опубликована: Июнь 7, 2023
Designing
of
molecules
for
drugs
is
important
topic
from
many
decades.
The
search
new
very
hard,
and
it
expensive
process.
Computer
assisted
framework
can
provide
the
fastest
way
to
design
screen
drug-like
compounds.
In
present
work,
a
multidimensional
approach
introduced
designing
screening
antioxidant
Antioxidants
play
crucial
role
in
ensuring
that
body's
oxidizing
reducing
species
are
kept
proper
balance,
minimizing
oxidative
stress.
Machine
learning
models
used
predict
activity.
Three
hydroxycinnamates
selected
as
standard
antioxidants.
Similar
compounds
searched
ChEMBL
database
using
chemical
structural
similarity
method.
libraries
generated
evolutionary
New
also
designed
automatic
decomposition
construction
building
blocks.
activity
all
predicted
machine
models.
space
envisioned
t-distributed
stochastic
neighbor
embedding
(t-SNE)
Best
shortlisted,
their
synthetic
accessibility
further
facilitate
experimental
chemists.
between
studied
fingerprints
heatmap.
Scientific Reports,
Год журнала:
2023,
Номер
13(1)
Опубликована: Сен. 15, 2023
Abstract
Cancer
is
one
of
the
leading
causes
death
worldwide,
making
early
detection
and
accurate
diagnosis
critical
for
effective
treatment
improved
patient
outcomes.
In
recent
years,
machine
learning
(ML)
has
emerged
as
a
powerful
tool
cancer
detection,
enabling
development
innovative
algorithms
that
can
analyze
vast
amounts
data
provide
predictions.
This
review
paper
aims
to
comprehensive
overview
various
ML
techniques
employed
highlighting
advancements,
challenges,
future
directions
in
this
field.
The
main
challenge
finding
safe,
auditable
reliable
analysis
method
fundamental
scientific
publication.
Food
contaminant
process
testing
food
products
identify
quantify
presence
harmful
substances
or
contaminants.
These
include
bacteria,
viruses,
toxins,
pesticides,
heavy
metals,
allergens,
other
chemical
residues.
Machine
artificial
intelligence
(A.I)
proposed
promising
possesses
excellent
potential
extract
information
with
high
validity
may
be
overlooked
conventional
its
capability
wide
range
investigations.
A.I
technology
used
meta-optics
develop
optical
devices
systems
higher
level
future.
Furthermore
(M.L.)
(A.I.)
play
key
roles
health
Approach
nano
materials
NMs
safety
assessment
environment
human
research.
Beside,
benefits
design
plasmonic
sensors
different
applications
resolution
are
convinced.
ACS Omega,
Год журнала:
2024,
Номер
9(6), С. 6403 - 6422
Опубликована: Фев. 2, 2024
Nonfullerene-based
organic
solar
cells
can
be
utilized
as
favorable
photovoltaic
and
optoelectronic
devices
due
to
their
enhanced
life
span
efficiency.
In
this
research,
seven
new
molecules
were
designed
improve
the
working
efficiency
of
by
utilizing
a
terminal
acceptor
modification
approach.
The
perceived
A2–D–A1–D–A2
configuration-based
possess
lower
band
gap
ranging
from
1.95
2.21
eV
compared
pre-existing
reference
molecule
(RW),
which
has
2.23
eV.
modified
also
exhibit
higher
λmax
values
672
768
nm
in
gaseous
715–839
solvent
phases,
respectively,
(RW)
molecule,
at
673
719
gas
chloroform
medium,
respectively.
ground
state
geometries,
molecular
planarity
parameter,
deviation
plane
analyzed
study
all
molecules.
natural
transition
orbitals,
density
state,
electrostatic
potential,
noncovalent
interactions,
frontier
matrix
analysis
studied
executed
validate
properties
these
Improved
charge
mobilities
dipole
moments
observed,
newly
possessed
internal
reorganization
energies.
open
circuit
voltage
(Voc)
W4,
W5,
W6,
W7
among
was
improved
molecule.
These
results
elaborate
on
superiority
novel-designed
over
potential
blocks
for
better
cell
applications.
Journal of Materials Chemistry C,
Год журнала:
2024,
Номер
12(11), С. 3811 - 3837
Опубликована: Янв. 1, 2024
Machine
learning
can
predict
the
properties
of
phase
change
azobenzene
derivatives
and
guide
molecular
design
to
further
improve
their
photothermal
conversion
performance.
