Constraints on the location of the liquid–liquid critical point in water
Nature Physics,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 3, 2025
Язык: Английский
Dissecting the Molecular Structure of the Air/Ice Interface from Quantum Simulations of the Sum-Frequency Generation Spectrum
Journal of the American Chemical Society,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 3, 2025
Ice
interfaces
are
pivotal
in
mediating
key
chemical
and
physical
processes
such
as
heterogeneous
reactions
the
environment,
ice
nucleation,
cloud
microphysics.
At
surface,
water
molecules
form
a
quasi-liquid
layer
(QLL)
with
properties
distinct
from
those
of
bulk.
Despite
numerous
experimental
theoretical
studies,
molecular-level
understanding
QLL
has
remained
elusive.
In
this
work,
we
use
state-of-the-art
quantum
dynamics
simulations
realistic
data-driven
many-body
potential
to
dissect
vibrational
sum-frequency
generation
(vSFG)
spectrum
air/ice
interface
terms
contributions
arising
individual
molecular
layers,
orientations,
hydrogen-bonding
topologies
that
determine
properties.
The
agreement
between
simulated
spectra
provides
picture
evolution
function
temperature
without
need
for
empirical
adjustments.
emergence
specific
features
vSFG
suggests
surface
restructuring
may
occur
at
lower
temperatures.
This
work
not
only
underscores
critical
role
interactions
nuclear
effects
surfaces
but
also
definitive
QLL,
which
plays
central
multiphase
relevance
range
fields,
including
atmospheric
chemistry,
cryopreservation,
materials
science.
Язык: Английский
MBX V1.2: Accelerating Data-Driven Many-Body Molecular Dynamics Simulations
Journal of Chemical Theory and Computation,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 14, 2025
The
MBX
software
provides
an
advanced
platform
for
molecular
dynamics
simulations,
leveraging
state-of-the-art
MB-pol
and
MB-nrg
data-driven
many-body
potential
energy
functions.
Developed
over
the
past
decade,
these
functions
integrate
physics-based
machine-learned
terms
trained
on
electronic
structure
data
calculated
at
"gold
standard"
coupled-cluster
level
of
theory.
Recent
advancements
in
have
focused
optimizing
its
performance,
resulting
release
v1.2.
While
inherently
nature
ensures
high
accuracy,
it
poses
computational
challenges.
v1.2
addresses
challenges
with
significant
performance
improvements,
including
enhanced
parallelism
that
fully
harnesses
power
modern
multicore
CPUs.
These
enable
simulations
nanosecond
time
scales
condensed-phase
systems,
significantly
expanding
scope
high-accuracy,
predictive
complex
systems
powered
by
Язык: Английский
Revealing the Water Structure at Neutral and Charged Graphene/Water Interfaces through Quantum Simulations of Sum Frequency Generation Spectra
Richa Rashmi,
Toheeb O. Balogun,
Golam Azom
и другие.
ACS Nano,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 21, 2025
The
structure
and
dynamics
of
water
at
charged
graphene
interfaces
fundamentally
influence
molecular
responses
to
electric
fields
with
implications
for
applications
in
energy
storage,
catalysis,
surface
chemistry.
Leveraging
the
realism
MB-pol
data-driven
many-body
potential
advanced
path-integral
quantum
dynamics,
we
analyze
vibrational
sum
frequency
generation
(vSFG)
spectrum
graphene/water
under
varying
charges.
Our
simulations
reveal
a
distinctive
dangling
OH
peak
vSFG
neutral
graphene,
consistent
recent
experimental
findings
yet
markedly
different
from
those
earlier
studies.
As
becomes
positively
charged,
interfacial
molecules
reorient,
decreasing
intensity
as
groups
turn
away
graphene.
In
contrast,
orient
their
bonds
toward
negatively
leading
prominent
corresponding
spectrum.
This
charge-induced
reorganization
generates
diverse
range
hydrogen-bonding
topologies
interface
driven
by
variations
underlying
electrostatic
interactions.
Importantly,
these
structural
changes
extend
into
deeper
layers,
creating
an
unequal
distribution
pointing
sheet.
imbalance
amplifies
bulk
spectral
features,
underscoring
complexity
interactions
that
shape
interfaces.
Язык: Английский
Neural Network-Based Molecular Dynamics Simulation of Water Assisted by Active Learning
The Journal of Physical Chemistry B,
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 2, 2025
In
our
study,
we
combined
classical
molecular
dynamics
(MD)
simulations
with
the
simulated
annealing
(SA)
method
to
explore
conformational
landscape
of
water
molecules.
By
using
K-means
clustering
method,
processed
MD
simulation
data
extract
representative
samples
structures
used
train
a
deep
potential
(DP)
model.
Our
DeePMD
showed
accuracy
in
predicting
structural
properties
compared
DFT-MD
results.
Meanwhile,
this
approach
achieves
balanced
prediction
density
and
self-diffusion
coefficients
earlier
simulations.
These
results
highlight
essential
role
sampling
techniques
training
DP
Furthermore,
demonstrated
effectiveness
combining
centroid
(CMD)
approach,
which
incorporates
nuclear
quantum
effects
(NQEs).
This
successfully
reproduced
shoulder
feature
at
3250
cm-1
Raman
spectra
for
O-H
stretch.
Incorporating
path
integral
into
underscores
importance
considering
NQEs
understanding
molecules'
dynamic
behaviors.
Язык: Английский
Electric Field’s Dueling Effects through Dehydration and Ion Separation in Driving NaCl Nucleation at Charged Nanoconfined Interfaces
Journal of the American Chemical Society,
Год журнала:
2025,
Номер
unknown
Опубликована: Май 9, 2025
Investigating
nucleation
in
charged
nanoconfined
environments
under
electric
fields
is
crucial
for
many
scientific
and
engineering
applications.
Here
we
study
the
of
NaCl
from
aqueous
solution
near
surfaces
using
machine-learning-augmented
enhanced
sampling
molecular
dynamics
simulations.
Our
simulations
successfully
drive
phase
transitions
between
liquid
solid
phases
NaCl.
The
stabilized
fields,
particularly
at
an
intermediate
surface
charge
density.
We
examine
which
physical
characteristics
solutions
find
that
removal
solvent
water
Cl-
precursor
plays
a
more
critical
role
than
accumulation
ions.
reveal
competing
effects
on
processes:
they
facilitate
water,
promoting
nucleation,
but
also
promote
separation
ion
pairs,
thereby
hindering
nucleation.
This
work
provides
framework
studying
processes
insights
design
electrochemistry
materials.
Язык: Английский
Structure making and breaking effects of ions on the anomalous diffusion of water revealed by machine learning potentials
Physical Chemistry Chemical Physics,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 1, 2025
The
dynamics
of
water
exhibits
anomalous
behavior
in
the
solvation
ions,
and
understanding
perturbation
that
ions
make
on
hydrogen
bond
structure
remains
an
open
question.
Язык: Английский
Scalable Super-hydrophobic Polyurethane/Fluorinated Polyurethane/SiO2 Nanofibrous Membranes for Waterproof and Breathable Application
Xi Yu,
Guiying Xu,
Jinfu Huang
и другие.
Fibers and Polymers,
Год журнала:
2025,
Номер
unknown
Опубликована: Май 24, 2025
Язык: Английский
Short-Range Δ-Machine Learning: A Cost-Efficient Strategy to Transfer Chemical Accuracy to Condensed Phase Systems
Journal of Chemical Theory and Computation,
Год журнала:
2025,
Номер
unknown
Опубликована: Май 28, 2025
DFT-based
machine-learning
potentials
(MLPs)
are
now
routinely
trained
for
condensed-phase
systems,
but
surpassing
DFT
accuracy
remains
challenging
due
to
the
cost
or
unavailability
of
periodic
reference
calculations.
Our
previous
work
(
Phys.
Rev.
Lett.
2022,
129,
226001)
demonstrated
that
high-accuracy
MLPs
can
be
within
CCMD
framework
using
extended
yet
finite
Here,
we
introduce
short-range
Δ-Machine
Learning
(srΔML),
a
method
starts
from
baseline
MLP
on
low-level
data
and
adds
Δ-MLP
correction
based
high-level
cluster
calculations
at
CC
level.
Applied
liquid
water,
srΔML
reduces
required
size
(H2O)64
(H2O)15
significantly
lowers
number
clusters
needed,
resulting
in
50-200×
reduction
computational
cost.
The
potential
closely
reproduces
target
accurately
captures
both
two-
three-body
structural
descriptors.
Язык: Английский