Software Practice and Experience,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 13, 2024
ABSTRACT
Methodology
Mathematica
provides
unique
symbolic
and
machine
learning
tools
for
developing
solving
mathematical
models
that
make
it
attractive
engineering
applications.
Chemical
engineers
frequently
have
a
need
to
update
process
design
software
with
custom
unit
operation
models.
This
paper
shows
two
new
methods
connect
chemical
simulators,
including
local
PC‐based
connection
cloud‐based
connection.
Both
are
discussed
in
detail
using
an
illustrative
example
of
membrane
separation
process.
We
also
demonstrate
how
the
between
Excel
facilitates
spreadsheet
calculations
while
enabling
simulator
software.
Furthermore,
all
shown
here
model‐independent
can
be
implemented
any
equation‐based
model
or
machine‐learning
when
adequate
training
data
is
available.
Results
Our
results
show
connected
simulators
such
as
CHEMCAD
Aspen
Plus.
The
performance
was
evaluated
by
direct
comparison
standard
already
exist
literature
To
date,
we
experimented
multicomponent
flash,
well‐mixed
However,
functionalized
simulator.
Conclusion
demonstrates
important
because
mathematics
available
Mathematica.
Link
Excel,
Wolfram
Cloud
Connector.
relatively
easy
implement
particularly
exciting
research
models,
if
one
wishes
use
proprietary
Communications Engineering,
Год журнала:
2025,
Номер
4(1)
Опубликована: Фев. 17, 2025
The
chemical
process
industry
(CPI)
faces
significant
challenges
in
improving
sustainability
and
efficiency
while
maintaining
conservative
principles
for
managing
cost,
complexity,
uncertainty.
This
work
introduces
a
data-driven
approach
to
dynamic
real-time
optimization
(D-RTO)
that
addresses
the
aforementioned
concerns
by
directly
extracting
policies
from
historical
plant
data.
Our
method
constructs
value
function
evaluate
trajectory
quality
employs
weighted
regression
derive
improved
policies.
When
applied
plant-wide
industrial
control
problem,
proposed
optimizer
demonstrates
superior
performance
adapting
disturbances
stability
product
quality.
These
results
challenge
conventional
assumptions
regarding
potential
of
CPI.
Although
limitations
exist
due
black-box
nature
neural
networks,
this
study
presents
promising
avenue
enhancing
operational
settings.
offers
practical
solution
optimization,
as
it
leverages
readily
available
data
does
not
require
extensive
modeling
efforts.
By
demonstrating
improvement
on
realistic
benchmark
paves
way
adoption
techniques
real-world
CPI
applications.
Alhazmi
Sarathy
report
complex
systems.
Their
provides
leveraging
without
requiring
Journal of Controlled Release,
Год журнала:
2024,
Номер
373, С. 962 - 966
Опубликована: Авг. 16, 2024
Formulation
scale-up
remains
a
major
hurdle
in
drug
development
part
because
preliminary
formulation
research
efforts
rarely
consider
the
challenges
of
scaling
up
production
for
commercialization.
This
Perspective
outlines
considerations
around
scalability
that
can
be
incorporated
into
design
work
order
to
increase
chances
successful
translation.
Both
technical
(unit
operations,
excipient
selection,
principles)
and
non-technical
(funding,
publications,
personnel)
are
discussed,
with
focus
on
lab-scale
by
academic
researchers.
ACS Energy Letters,
Год журнала:
2024,
Номер
9(11), С. 5550 - 5561
Опубликована: Окт. 25, 2024
The
field
of
CO2
reduction
has
identified
several
challenges
that
must
be
overcome
to
realize
its
immense
potential
simultaneously
close
the
carbon
cycle,
replace
fossil-based
chemical
feedstocks,
and
store
renewable
electricity.
However,
frequently
cited
research
targets
were
set
without
quantitatively
analyzing
their
impact
on
economic
viability.
Through
a
physics-informed
techno-economic
assessment,
we
offer
guidance
top
priorities
for
reduction.
Although
separations
dominate
capital
cost,
increasing
single-pass
conversion
is
unnecessary
because
it
leads
selectivity
loss
in
current
membrane
electrode
assemblies.
Decoupling
by
moving
away
from
plug
flow
reactor
design
would
reduce
base
case
levelized
cost
$1.22/kgCO
$0.97/kgCO,
as
impactful
eliminating
CO2R
overpotential.
Operating
at
high
densities
(>500
mA/cm2)
undesirable
unless
cell
voltages
can
lowered.
We
confirm
product
dominated
electricity
drive
electrolysis.
wholesale
wind
solar
are
cheaper
than
retail
electricity,
capacity
factors
too
low
economical
operation.
Adding
energy
storage
increase
factor
triples
process.
By
updating
based
fundamental
electrolyzer
behavior,
hope
this
work
accelerates
practical
application
Cell Reports Physical Science,
Год журнала:
2024,
Номер
5(3), С. 101859 - 101859
Опубликована: Март 1, 2024
The
development
of
sustainable
chemical
processes
is
critical
for
society
to
supply
commercial
chemicals
with
limited
natural
resources.
Here,
we
report
catalytic
reactions
that
are
developed
upgrade
lignocellulosic
biomass
into
a
pharmaceutical
ingredient
(rehmanone
A)
and
monomers.
Biomass-derived
glucose
dissolved
in
an
acetone/water
co-solvent
used
as
feed
sequential
isomerization
dehydration
produce
5-hydroxymethyl
furfural
(HMF).
This
HMF
reacted
acetone
aldol-condensed
intermediate
(HAH,
adduct
two
one
acetone)
94%
isolation
yield.
diol
group
HAH
etherified
methanol
synthesize
rehmanone
A
95%
reaction
Alternatively,
the
C=C
bonds
hydrogenated
monomers,
such
partially
fully
84%
93%
yields,
respectively.
experimental
parameters
assess
economic
potential
these
synthesis-based
by
techno-economic
analyses
toll
manufacturing
scenario.
Deleted Journal,
Год журнала:
2024,
Номер
1(1), С. 010201 - 010201
Опубликована: Июнь 7, 2024
IOP
journal
sustainability
science
and
technology
(sus
sci
tech)
in
2024
beyond:
equitable
publishing
aligned
with
United
Nations'
sustainable
development
goals
(SDGs),
Jonas
Baltrusaitis,
Bhavik
Bakashi,
Katarzyna
Chojnacka,
Christopher
Chuck,
Marc-Olivier
Coppens,
Jacqueline
Sophie
Edge,
Gavin
Harper,
Benjamin
Hsiao,
Hao
Li,
Mark
Mba-Wright,
Michael
McLaughlin,
Arpita
Nandy,
Shu-Yuan
Pan
(潘述元),
Zhe
Qiang,
Cauê
Ribeiro
de
Oliveira,
Malgorzata
Swadzba-Kwasny,
Meng
Wang,
Yizhi
Xiang,
Lizhi
Zhang
Frontiers in Chemical Engineering,
Год журнала:
2024,
Номер
6
Опубликована: Авг. 29, 2024
Recent
advances
in
generative
artificial
intelligence
(GenAI),
particularly
large
language
models
(LLMs),
are
profoundly
impacting
many
fields.
In
chemical
engineering,
GenAI
plays
a
pivotal
role
the
design,
scale-up,
and
optimization
of
biochemical
processes.
The
natural
understanding
capabilities
LLMs
enable
interpretation
complex
biological
data.
Given
rapid
developments
GenAI,
this
paper
explores
extensive
applications
multiscale
spanning
from
quantum
mechanics
to
macro-level
optimization.
At
molecular
levels,
accelerates
discovery
novel
products
enhances
fundamental
phenomena.
larger
scales,
improves
process
design
operational
efficiency,
contributing
sustainable
practices.
We
present
several
examples
demonstrate
including
its
impact
on
nanomaterial
hardness
enhancement,
catalyst
generation,
protein
development
autonomous
experimental
platforms.
This
integration
demonstrates
potential
address
challenges,
drive
innovation,
foster
advancements
engineering.
