ACS Engineering Au,
Год журнала:
2023,
Номер
3(6), С. 364 - 390
Опубликована: Окт. 22, 2023
This
perspective
provides
the
collective
opinions
of
a
dozen
chemical
reaction
engineers
from
academia
and
industry.
In
this
sequel
to
"Vision
2020:
Reaction
Engineering
Roadmap,"
published
in
2001,
we
provide
our
about
field
engineering
by
addressing
current
situation,
identifying
barriers
progress,
recommending
research
directions
context
four
industry
sectors
(basic
chemicals,
specialty
pharmaceuticals,
polymers)
five
technology
areas
(reactor
system
selection,
design
scale-up,
mechanism
development
property
estimation,
catalysis,
nonstandard
reactor
types,
electrochemical
systems).
Our
input
report
includes
numerous
recommendations
regarding
needs
coming
decades,
including
guidance
for
prioritizing
efforts
workforce
development,
measurement
science,
computational
methods.
We
see
important
roles
plastics
circularity
challenge,
decarbonization
processes,
electrification
reactors,
conversion
batch
processes
continuous
intensified,
dynamic
processes.
Bioresource Technology,
Год журнала:
2022,
Номер
367, С. 128255 - 128255
Опубликована: Ноя. 5, 2022
Pine
needles
(PNs)
are
one
of
the
largest
bio-polymer
produced
worldwide.
Its
waste,
i.e.,
fallen
PNs,
is
mostly
responsible
for
forest
fires
and
a
major
challenge.
In
present
article,
we
have
reviewed
differenteffortsmadeto
tackle
this
situation.
PNs
been
used
in
various
fields
such
asin
composite,
water
purification
industries,electronic
devices,
etc.
Gasification
appealing
processes
turning
into
bio-energy;
pyrolysis
technique
has
employed
to
create
carbon-based
materials;
saccharification
combined
with
fermentation
good
yields
bio-ethanol;
Pd
or
Ni/PNs
biocatalyst
showed
catalytic
properties
variousreactionsand
without
catalyst
an
alluring
prepare
bio-fuel.
Nano
cellulose
extracted
from
thermal
mechanical
strength.
The
air
quality
nearbyenvironment
was
examinedby
studying
magnetic
PNs.
Packing
materials
made
exceptional
ethylene
scavenging
abilities.
Energy & Fuels,
Год журнала:
2024,
Номер
38(4), С. 2654 - 2689
Опубликована: Фев. 2, 2024
The
rapid
depletion
of
fossil-derived
fuels
along
with
rising
environmental
pollution
have
motivated
academics
and
manufacturers
to
pursue
more
environmentally
friendly
sustainable
energy
options
in
today's
globe.
Biodiesel
has
developed
as
an
ecologically
favorable
alternative.
However,
the
mass
manufacturing
biodiesel
on
industrial
scale
confronts
substantial
cost
pricing
challenges.
To
address
this
issue,
high-efficiency
catalysts
a
large
number
active
sites
are
needed,
resulting
increased
output
quality.
Metal–organic
frameworks
(MOFs)
received
lot
interest
catalyst
for
converting
oils/fats
or
fatty
acids
into
biodiesel.
MOFs
polyporous
materials
that
can
alter
pore
size
well
topological
structure.
They
serve
versatile
foundation
designing
satisfy
unique
needs
catalytic
reactions
conversion
pathways.
purpose
current
work
is
shed
light
underlying
mechanisms
essential
properties
MOF-based
used
synthesis.
In
addition,
several
methods
connecting
inside
scrutinized,
while
usability
production
process
completely
compared
other
catalysts.
More
importantly,
limits
future
research
directions
about
utilization
synthesis
route
also
critically
presented.
general,
review
contributes
improved
awareness
potential
sector
by
investigating
primary
mechanism
characteristics
Case Studies in Thermal Engineering,
Год журнала:
2022,
Номер
40, С. 102448 - 102448
Опубликована: Сен. 24, 2022
The
thermal
performance
of
a
flat
plate
solar
collector
using
MWCNT
+
Fe3O4/Water
hybrid
nanofluids
was
examined
in
this
research.
tested
different
nanofluid
concentrations
and
flow
rates
an
arid
environment.
A
significant
enhancement
coefficient
heat
transfer
(26.3%)
with
marginal
loss
on
pressure
drop
due
to
friction
factor
(18.9%).
data
collected
during
experimental
testing
utilized
develop
novel
prediction
models
for
efficient
transfer,
Nusselt's
number,
factor,
efficiency.
modern
ensemble
machine
learning
techniques
Boosted
Regression
Tree
(BRT)
Extreme
Gradient
Boosting
(XGBoost)
were
used
prognostic
each
parameter.
battery
statistical
methods
Taylor's
graphs
compare
the
these
two
ML
techniques.
value
R2
BRT-based
0.9619
-
0.9994
0.9914
0.9997
XGBoost-based
models.
mean
squared
error
quite
low
all
(0.000081
9.11),
while
absolute
percentage
negligible
from
0.0025
0.3114.
comprehensive
analysis
model
complemented
improved
comparison
paradigm,
reveal
superiority
XGBoost
over
BRT.
