Applying statistical modeling strategies to sparse datasets in synthetic chemistry
Science Advances,
Journal Year:
2025,
Volume and Issue:
11(1)
Published: Jan. 1, 2025
The
application
of
statistical
modeling
in
organic
chemistry
is
emerging
as
a
standard
practice
for
probing
structure-activity
relationships
and
predictive
tool
many
optimization
objectives.
This
review
aimed
tutorial
those
entering
the
area
chemistry.
We
provide
case
studies
to
highlight
considerations
approaches
that
can
be
used
successfully
analyze
datasets
low
data
regimes,
common
situation
encountered
given
experimental
demands
Statistical
hinges
on
(what
being
modeled),
descriptors
(how
are
represented),
algorithms
modeled).
Herein,
we
focus
how
various
reaction
outputs
(e.g.,
yield,
rate,
selectivity,
solubility,
stability,
turnover
number)
structures
binned,
heavily
skewed,
distributed)
influence
choice
algorithm
constructing
chemically
insightful
models.
Language: Английский
COBRA web application to benchmark linear regression models for catalyst optimization with few-entry datasets
Cell Reports Physical Science,
Journal Year:
2024,
Volume and Issue:
unknown, P. 102348 - 102348
Published: Dec. 1, 2024
Language: Английский
Active Learning Guided Optimization of Frontal Ring-Opening Metathesis Polymerization via Alkylidene Modification
ACS Macro Letters,
Journal Year:
2025,
Volume and Issue:
unknown, P. 525 - 531
Published: April 11, 2025
Frontal
ring-opening
metathesis
polymerization
(FROMP)
offers
an
energy-efficient
method
for
manufacturing
high-performance
thermoset
resins.
However,
the
background
reaction
attributed
to
(ROMP)
results
in
a
complex
trade-off
between
resin
shelf
life─necessary
practical
manufacturability─and
front
velocity.
Here,
we
study
influence
of
alkylidene
ligand
selection
Grubbs'
second-generation
Ru-initiators
on
kinetics
FROMP
and
ROMP.
We
reveal
that
identity
differentially
affects
ROMP
reactivity,
enabling
tunable
control
over
pot
life
speed.
Leveraging
this
insight,
use
active
learning
with
multiobjective
Bayesian
optimization
efficiently
explore
design
space
identify
superior
formulations.
This
work
advances
rational
resins,
expanding
range
accessible
formulations
accelerating
discovery
materials
applications.
Language: Английский
Data Science Meets Ziegler–Natta Catalysis to Design High-Performance Lewis Bases for Isotactic Polypropylene Production
ACS Catalysis,
Journal Year:
2025,
Volume and Issue:
unknown, P. 8185 - 8193
Published: May 1, 2025
Language: Английский
Frontal polymerization of thermosets to enable vacuum-formed structural electronics
Nature Communications,
Journal Year:
2025,
Volume and Issue:
16(1)
Published: May 5, 2025
Language: Английский
A Straightforward and Rapid Method to Assess ROMP Performance in Neat Thermosetting Resins
Benjamin Godwin,
No information about this author
Dylan Bouëtard,
No information about this author
Jakub Talcik
No information about this author
et al.
ACS Applied Polymer Materials,
Journal Year:
2024,
Volume and Issue:
7(1), P. 377 - 385
Published: Dec. 23, 2024
Polydicyclopentadiene
(PDCPD)
is
a
thermosetting
material
used
to
produce
body
panels
for
industrial
equipment
and
vehicles.
PDCPD
other
important
thermosets
are
produced
by
direct
transformation
of
neat
monomer
(dicyclopentadiene)
solid
polymer
using
catalyst
in
process
called
reaction
injection
molding.
As
polymerization
cross-linking
competitive,
the
therefore
inherently
challenging
study.
In
this
work,
we
develop
laboratory-scale
method
that
rapid
low
cost,
which
enables
comparison
initiators
ring-opening
metathesis
polymerization.
Additionally,
prediction
both
mechanical
thermal
properties
final
material.
Language: Английский