ACS Sustainable Chemistry & Engineering,
Год журнала:
2024,
Номер
12(21), С. 7987 - 8000
Опубликована: Май 13, 2024
Deep
eutectic
solvents
(DESs)
are
gaining
recognition
as
environmentally
friendly
solvent
alternatives
for
diverse
chemical
processes.
Yet,
designing
DESs
tailored
to
specific
applications
is
a
resource-intensive
task,
which
requires
an
accurate
estimation
of
their
physicochemical
properties.
Among
them,
viscosity
crucial,
it
often
dictates
DES's
suitability
solvent.
In
this
study,
artificial
neural
network
(ANN)
introduced
accurately
describe
the
and
mixtures
with
cosolvents.
The
ANN
utilizes
molecular
parameters
derived
from
σ-profiles,
computed
using
conductor-like
screening
model
real
segment
activity
coefficient
(COSMO-SAC).
data
set
comprises
1891
experimental
measurements
48
based
on
choline
chloride,
encompassing
279
different
compositions,
along
1618
points
DES
cosolvents
water,
methanol,
isopropanol,
dimethyl
sulfoxide,
covering
wide
range
0.3862
4722
mPa
s.
optimal
structure
describing
logarithmic
configured
9-19-16-1,
achieving
overall
average
absolute
relative
deviation
1.6031%.
More
importantly,
shows
remarkable
extrapolation
capacity,
capable
predicting
systems
including
(ethanol)
hydrogen
bond
donors
(2,3-butanediol)
not
considered
in
training.
also
demonstrates
extensive
applicability
domain,
94.17%
entire
database.
These
achievements
represent
significant
step
forward
developing
robust,
open
source,
highly
models
descriptors.
Molecules,
Год журнала:
2024,
Номер
29(10), С. 2296 - 2296
Опубликована: Май 14, 2024
Deep
eutectic
solvents
(DESs)
are
commonly
used
in
pharmaceutical
applications
as
excellent
solubilizers
of
active
substances.
This
study
investigated
the
tuning
ibuprofen
and
ketoprofen
solubility
utilizing
DESs
containing
choline
chloride
or
betaine
hydrogen
bond
acceptors
various
polyols
(ethylene
glycol,
diethylene
triethylene
glycerol,
1,2-propanediol,
1,3-butanediol)
donors.
Experimental
data
were
collected
for
all
DES
systems.
A
machine
learning
model
was
developed
using
COSMO-RS
molecular
descriptors
to
predict
solubility.
All
studied
exhibited
a
cosolvency
effect,
increasing
drug
at
modest
concentrations
water.
The
accurately
predicted
ibuprofen,
ketoprofen,
related
analogs
(flurbiprofen,
felbinac,
phenylacetic
acid,
diphenylacetic
acid).
approach
enables
rational
design
prediction
formulations
improved
applications.
Batteries,
Год журнала:
2024,
Номер
10(2), С. 45 - 45
Опубликована: Янв. 27, 2024
Urea,
a
basic
chemical
compound,
holds
diverse
applications
across
numerous
domains,
ranging
from
agriculture
to
energy
storage.
Of
particular
interest
is
its
role
as
hydrogen
bond
donor
(HBD).
This
specific
characteristic
has
propelled
utilization
an
essential
component
in
crafting
deep
eutectic
solvents
(DESs)
for
battery
electrolytes.
Incorporating
urea
into
DESs
presents
promising
avenue
address
environmental
concerns
associated
with
traditional
electrolytes,
thereby
advancing
technology.
Conventional
often
composed
of
hazardous
and
combustible
solvents,
pose
significant
risks
upon
improper
disposal
potentially
contaminating
soil
water
threatening
both
human
health
ecosystems.
Consequently,
there
pressing
need
eco-friendly
alternatives
capable
upholding
high
performance
safety
standards.
DESs,
categorized
organic
salts
resulting
the
blending
two
or
more
compounds,
have
emerged
contenders
next
generation
Urea
stands
out
among
DES
electrolytes
by
enhancing
ion
transport,
widening
electrochemical
window
stability
(ESW),
prolonging
cycle
life.
Further,
non-toxic
nature,
limited
flammability,
elevated
thermal
play
pivotal
roles
mitigating
issues
Laboratory
testing
urea-based
various
systems,
including
Al-ion,
Na-ion,
Zn-ion
batteries,
already
been
demonstrated.
review
examines
evolution
elucidating
their
structure,
molecular
interaction
mechanisms,
attributes,
preparation
methodologies.
Journal of Chromatography Open,
Год журнала:
2024,
Номер
5, С. 100131 - 100131
Опубликована: Апрель 15, 2024
Since
ancient
times,
humanity
has
used
plants
to
cure
diseases
or
maintain
health.
Nowadays,
obtaining
the
bioactive
components
of
and
researching
their
effects
continues
at
great
speed.
Plant-derived
chemicals
are
studied
with
interest
in
food,
pharmaceutical
cosmetic
industries.
The
complexity
city
life
limits
access
natural
habitat.
Nutraceuticals
indispensable
products
our
age
protect
Many
methods
have
been
developed
successfully
applied
for
extracting
crude
plant
extracts
pure
active
substances
included
nutraceuticals
from
tissues
quantitative
analysis.
This
study
compiled
ingredients
techniques
analyzing
compounds.
extraction
plant-based
(maceration,
Soxhlet
extraction,
decoction,
infusion,
hydro
distillation,
ultrasound-assisted
(UAE),
microwave-assisted
(MAE),
enzyme-assisted
(EAE),
pressurized
liquid
(PLE),
supercritical
fluid
(SFE))
were
explained
detail,
some
important
source
summarized
table
form.
Additionally,
studies
using
different
analytical
such
as
high-performance
chromatography
(HPLC),
gas
(GC),
thin
layer
(TLC),
mass
spectrometry
(MS),
ultra-performance
(UPLC)
discussed.
Finally,
evaluating
its
effectiveness
compounds
prospects
more
environmentally
friendly
alternative
traditional
solvents
emphasized.
review
covers
latest
practices
new
trends
over
last
three
years.
ACS Sustainable Chemistry & Engineering,
Год журнала:
2024,
Номер
12(21), С. 7987 - 8000
Опубликована: Май 13, 2024
Deep
eutectic
solvents
(DESs)
are
gaining
recognition
as
environmentally
friendly
solvent
alternatives
for
diverse
chemical
processes.
Yet,
designing
DESs
tailored
to
specific
applications
is
a
resource-intensive
task,
which
requires
an
accurate
estimation
of
their
physicochemical
properties.
Among
them,
viscosity
crucial,
it
often
dictates
DES's
suitability
solvent.
In
this
study,
artificial
neural
network
(ANN)
introduced
accurately
describe
the
and
mixtures
with
cosolvents.
The
ANN
utilizes
molecular
parameters
derived
from
σ-profiles,
computed
using
conductor-like
screening
model
real
segment
activity
coefficient
(COSMO-SAC).
data
set
comprises
1891
experimental
measurements
48
based
on
choline
chloride,
encompassing
279
different
compositions,
along
1618
points
DES
cosolvents
water,
methanol,
isopropanol,
dimethyl
sulfoxide,
covering
wide
range
0.3862
4722
mPa
s.
optimal
structure
describing
logarithmic
configured
9-19-16-1,
achieving
overall
average
absolute
relative
deviation
1.6031%.
More
importantly,
shows
remarkable
extrapolation
capacity,
capable
predicting
systems
including
(ethanol)
hydrogen
bond
donors
(2,3-butanediol)
not
considered
in
training.
also
demonstrates
extensive
applicability
domain,
94.17%
entire
database.
These
achievements
represent
significant
step
forward
developing
robust,
open
source,
highly
models
descriptors.
