Energies,
Год журнала:
2024,
Номер
17(17), С. 4506 - 4506
Опубликована: Сен. 8, 2024
Additives
for
anaerobic
digestion
(AD)
can
play
a
significant
role
in
optimizing
the
process
by
increasing
biogas
production,
stabilizing
system,
and
improving
digestate
quality.
The
of
additives
largely
boils
down
to,
among
others,
enhancing
direct
interspecies
electron
transfer
(DIET)
between
microbial
communities,
resulting
improved
syntrophic
interactions,
adsorption
toxic
substances
that
may
inhibit
activity,
stability
accelerating
decomposition
complex
organic
materials,
thereby
rate
hydrolysis.
Through
aforementioned
action,
significantly
affect
AD
performance.
function
these
materials
varies,
from
activity
to
maintaining
optimal
conditions
protecting
system
inhibitors.
choice
should
be
carefully
tailored
specific
needs
digester
maximize
benefits
ensure
sustainability.
In
light
considerations,
this
paper
characterizes
most
commonly
used
their
combinations
based
on
comprehensive
review
recent
scientific
publications,
including
report
results
conducted
studies.
publication
features
chapters
describe
carbon-based
conductive
metal
oxide
nanomaterials,
trace
metal,
biological
additives,
enzymes
microorganisms.
It
concludes
with
summarising
reports
various
discussing
functional
properties,
as
well
advantages
disadvantages.
presented
is
substantive
concise
analysis
latest
knowledge
process.
application
characterized
great
potential;
hence,
subject
matter
very
current
future-oriented.
Abstract
The
utilization
of
biochar
derived
from
biomass
residue
to
enhance
anaerobic
digestion
(AD)
for
bioenergy
recovery
offers
a
sustainable
approach
advance
energy
and
mitigate
climate
change.
However,
conducting
comprehensive
research
on
the
optimal
conditions
AD
experiments
with
addition
poses
challenge
due
diverse
experimental
objectives.
Machine
learning
(ML)
has
demonstrated
its
effectiveness
in
addressing
this
issue.
Therefore,
it
is
essential
provide
an
overview
current
ML-optimized
processes
biochar-enhanced
order
facilitate
more
systematic
ML
tools.
This
review
comprehensively
examines
material
flow
preparation
impact
comprehension
reviewed
optimize
production
process
perspective.
Specifically,
summarizes
application
techniques,
based
artificial
intelligence,
predicting
yield
properties
residues,
as
well
their
AD.
Overall,
analysis
address
challenges
recovery.
In
future
research,
crucial
tackle
that
hinder
implementation
pilot-scale
reactors.
It
recommended
further
investigate
correlation
between
physicochemical
process.
Additionally,
enhancing
role
throughout
entire
holds
promise
achieving
economically
environmentally
optimized
efficiency.
Graphical
