Chemical Engineering Communications,
Год журнала:
2024,
Номер
unknown, С. 1 - 31
Опубликована: Дек. 30, 2024
Research
focus
has
turned
to
sustainable
and
ecologically
friendly
energy
sources
due
the
growing
dependence
on
nonrenewable
fuels.
The
lignocellulosic
biomass's
(LCB)
intrinsic
recalcitrance
makes
bioprocess's
downstream
processing
difficult.
Over
past
20
years,
pretreatment
procedures
have
drawn
a
lot
of
attention
since
they
are
acknowledged
as
essential
operations
for
effective
biomass
refining.
In
order
achieve
more
practices,
deep
eutectic
solvents
(DESs)
proven
be
useful
LCB
valorization.
DESs
thermochemically
stable,
recyclable,
non-flammable,
contain
very
little
vapor
pressure.
present
article,
an
extensive
summarization
types,
characteristics,
functions
in
efficient
conversion
sugarcane
bagasse
is
reviewed.
addition
outlining
principles
DES
composition,
overview
provided
factors
influencing
ChCl-DES-assisted
extraction
compositional
components
from
bagasse.
Furthermore,
in-depth
insight
into
mechanism
behind
ChCl-based-DES
reactions
will
provide
highlights
future
studies.
most
recent
advancements
years
2018–2023
DES-based
valorization
various
products
then
thoroughly
covered.
Finally,
paper
concluded
with
discussion
technical
issues
potential
directions
research
works.
Abstract
Lignocellulose
biomass,
Earth's
most
abundant
renewable
resource,
is
crucial
for
sustainable
production
of
high–value
chemicals
and
bioengineered
materials,
especially
energy
storage.
Efficient
pretreatment
vital
to
boost
lignocellulose
conversion
bioenergy
biomaterials,
cut
costs,
broaden
its
energy–sector
applications.
Machine
learning
(ML)
has
become
a
key
tool
in
this
field,
optimizing
processes,
improving
decision‐making,
driving
innovation
valorization
This
review
explores
main
strategies
–
physical,
chemical,
physicochemical,
biological,
integrated
methods
evaluating
their
pros
cons
It
also
stresses
ML's
role
refining
these
supported
by
case
studies
showing
effectiveness.
The
examines
challenges
opportunities
integrating
ML
into
storage,
underlining
pretreatment's
importance
unlocking
lignocellulose's
full
potential.
By
blending
process
knowledge
with
advanced
computational
techniques,
work
aims
spur
progress
toward
sustainable,
circular
bioeconomy,
particularly
storage
solutions.
Molecules,
Год журнала:
2024,
Номер
29(21), С. 5073 - 5073
Опубликована: Окт. 26, 2024
The
valorization
and
dissolution
of
lignin
using
ionic
liquids
(ILs)
is
critical
for
developing
sustainable
biorefineries
a
circular
bioeconomy.
This
review
aims
to
critically
assess
the
current
state
computational
machine
learning
methods
understanding
optimizing
IL-based
processes
reported
since
2022.
paper
examines
various
approaches,
from
quantum
chemistry
learning,
highlighting
their
strengths,
limitations,
recent
advances
in
predicting
lignin-IL
interactions.
Key
themes
include
challenges
accurately
modeling
lignin’s
complex
structure,
development
efficient
screening
methodologies
enhance
processes,
integration
with
calculations.
These
will
drive
progress
by
providing
deeper
molecular-level
insights
facilitating
rapid
novel
IL-lignin
systems.
