10 research outputs found
Ultrafast Chemistry under Nonequilibrium Conditions and the Shock to Deflagration Transition at the Nanoscale
We use molecular dynamics simulations
to describe the chemical
reactions following shock-induced collapse of cylindrical pores in
the high-energy density material RDX. For shocks with particle velocities
of 2 km/s we find that the collapse of a 40 nm diameter pore leads
to a deflagration wave. Molecular collisions during the collapse lead
to ultrafast, multistep chemical reactions that occur under nonequilibrium
conditions. Exothermic products formed during these first few picoseconds
prevent the nanoscale hotspot from quenching. Within 30 ps, a local
deflagration wave develops; it propagates at 0.25 km/s and consists
of an ultrathin reaction zone of only ∼5 nm, thus involving
large temperature and composition gradients. Contrary to the assumptions
in current models, a static thermal hotspot matching the dynamical
one in size and thermodynamic conditions fails to produce a deflagration
wave indicating the importance of nonequilibrium loading in the criticality
of nanoscale hot spots. These results provide insight into the initiation
of reactive decomposition
Configurational-Bias Monte Carlo Back-Mapping Algorithm for Efficient and Rapid Conversion of Coarse-Grained Water Structures into Atomistic Models
Coarse-grained
molecular dynamics (MD) simulations represent a
powerful approach to simulate longer time scale and larger length
scale phenomena than those accessible to all-atom models. The gain
in efficiency, however, comes at the cost of atomistic details. The
reverse transformation, also known as back mapping, of coarse-grained
beads into their atomistic constituents represents a major challenge.
Most existing approaches are limited to specific molecules or specific
force fields and often rely on running a long-time atomistic MD of
the back-mapped configuration to arrive at an optimal solution. Such
approaches are problematic when dealing with systems with high diffusion
barriers. Here, we introduce a new extension of the configurational-bias
Monte Carlo (CBMC) algorithm, which we term the crystalline-configurational-bias
Monte Carlo (C-CBMC) algorithm, which allows rapid and efficient conversion
of a coarse-grained model back into its atomistic representation.
Although the method is generic, we use a coarse-grained water model
as a representative example and demonstrate the back mapping or reverse
transformation for model systems ranging from the ice–liquid
water interface to amorphous and crystalline ice configurations. A
series of simulations using the TIP4P/Ice model are performed to compare
the new CBMC method to several other standard Monte Carlo and molecular
dynamics-based back-mapping techniques. In all of the cases, the C-CBMC
algorithm is able to find optimal hydrogen-bonded configuration many
thousand evaluations/steps sooner than the other methods compared
within this paper. For crystalline ice structures, such as a hexagonal,
cubic, and cubic-hexagonal stacking disorder structures, the C-CBMC
was able to find structures that were between 0.05 and 0.1 eV/water
molecule lower in energy than the ground-state energies predicted
by the other methods. Detailed analysis of the atomistic structures
shows a significantly better global hydrogen positioning when contrasted
with the existing simpler back-mapping methods. The errors in the
radial distribution functions (RDFs) of back-mapped configuration
relative to reference configuration for the C-CBMC, MD, and MC were
found to be 6.9, 8.7, and 12.9, respectively, for the hexagonal system.
For the cubic system, the relative errors of the RDFs for the C-CBMC,
MD, and MC were found to be 18.2, 34.6, and 39.0, respectively. Our
results demonstrate the efficiency and efficacy of our new back-mapping
approach, especially for crystalline systems where simple force-field-based
relaxations have a tendency to get trapped in local minima
Exothermic Self-Sustained Waves with Amorphous Nickel
The
synthesis of amorphous Ni (a-Ni) using a liquid-phase chemical reduction
approach is reported. Detailed structural analysis indicates that
this method allows for efficient fabrication of high surface area
(210 m<sup>2</sup>/g) amorphous Ni nanopowder with low impurity content.
We investigated the self-propagating exothermic waves associated with
crystallization of Ni from the amorphous precursor. Time-resolved
X-ray diffraction indicates that amorphous nickel crystallizes in
the temperature range 445–480 K. High-speed infrared imaging
reveals that local preheating of compressed a-Ni nanopowder triggers
a self-sustaining crystallization wave that propagates with velocity
∼0.3 mm/s. The maximum temperature of crystallization wave
depends on the sample density and can be as high as 600 K. The Kissinger
approach is used to determine the apparent activation energy (55.4 ±
4 kJ/mol) of crystallization. The self-diffusion activation energy
of Ni atoms in a-Ni is ∼60 kJ/mol, determined through molecular
dynamics (MD) simulations. This agreement of experimentally derived
and theoretically calculated activation energies allows us to conclude
that self-diffusion of Ni atoms is the rate-limiting stage for crystallization.
Furthermore, utilization of amorphous metal as a reactant significantly
increases the rate of solid-state reactions. For example, in reactive
intermetallic forming systems, such as Ni + Al, the self-sustaining
reaction propagation velocity with a-Ni is twice higher than with
crystalline Ni of the same morphology. Additionally, using a-Ni increases
the maximum reaction temperature in the Ni + Al system by 300 K
<i>Ab Initio</i>-Based Bond Order Potential to Investigate Low Thermal Conductivity of Stanene Nanostructures
We
introduce a bond order potential (BOP) for stanene based on
an <i>ab initio</i> derived training data set. The potential
is optimized to accurately describe the energetics, as well as thermal
and mechanical properties of a free-standing sheet, and used to study
diverse nanostructures of stanene, including tubes and ribbons. As
a representative case study, using the potential, we perform molecular
dynamics simulations to study stanene’s structure and temperature-dependent
thermal conductivity. We find that the structure of stanene is highly
rippled, far in excess of other 2-D materials (e.g., graphene), owing
to its low in-plane stiffness (stanene: ∼ 25 N/m; graphene:
∼ 480 N/m). The extent of stanene’s rippling also shows
stronger temperature dependence compared to that in graphene. Furthermore,
we find that stanene based nanostructures have significantly lower
thermal conductivity compared to graphene based structures owing to
their softness (i.e., low phonon group velocities) and high anharmonic
response. Our newly developed BOP will facilitate the exploration
of stanene based low dimensional heterostructures for thermoelectric
and thermal management applications
Three-dimensional Hard X-ray Ptychographic Reflectometry Imaging on Extended Mesoscopic Surface Structures
Many nano and quantum devices, with their sizes often spanning from millimeters down to sub-nanometer, have intricate low-dimensional, non-uniform, or hierarchical structures on surfaces and interfaces. Since their functionalities are dependent on these structures, high-resolution surface-sensitive characterization becomes imperative to gain a comprehensive understanding of the function-structure relationship. We thus developed hard X-ray ptychographic reflectometry imaging, a new technique that merges the high-resolution two-dimensional imaging capabilities of hard X-ray ptychography for extended objects, with the high-resolution depth profiling capabilities of X-ray reflectivity for layered structures. The synergy of these two methods fully leverages both amplitude and phase information from ptychography reconstruction to not only reveal surface topography and localized structures such as shapes and electron densities, but also yields statistical details such as interfacial roughness that is not readily accessible through coherent imaging solely. The hard X-ray ptychographic reflectometry imaging is well-suited for three-dimensional imaging of mesoscopic samples, particularly those comprising planar or layered nanostructures on opaque supports, and could also offer a high-resolution surface metrology and defect analysis on semiconductor devices such as integrated nanocircuits and lithographic photomasks for microchip fabrications
Defect Dynamics in 2‑D MoS<sub>2</sub> Probed by Using Machine Learning, Atomistic Simulations, and High-Resolution Microscopy
Structural
defects govern various physical, chemical, and optoelectronic
properties of two-dimensional transition-metal dichalcogenides (TMDs).
A fundamental understanding of the spatial distribution and dynamics
of defects in these low-dimensional systems is critical for advances
in nanotechnology. However, such understanding has remained elusive
primarily due to the inaccessibility of (a) necessary time scales <i>via</i> standard atomistic simulations and (b) required spatiotemporal
resolution in experiments. Here, we take advantage of supervised machine
learning, <i>in situ</i> high-resolution transmission electron
microscopy (HRTEM) and molecular dynamics (MD) simulations to overcome
these limitations. We combine genetic algorithms (GA) with MD to investigate
the extended structure of point defects, their dynamical evolution,
and their role in inducing the phase transition between the semiconducting
(2H) and metallic (1T) phase in monolayer MoS<sub>2</sub>. GA-based
structural optimization is used to identify the long-range structure
of randomly distributed point defects (sulfur vacancies) for various
defect densities. Regardless of the density, we find that organization
of sulfur vacancies into extended lines is the most energetically
favorable. HRTEM validates these findings and suggests a phase transformation
from the 2H-to-1T phase that is localized near these extended defects
when exposed to high electron beam doses. MD simulations elucidate
the molecular mechanism driving the onset of the 2H to 1T transformation
and indicate that finite amounts of 1T phase can be retained by increasing
the defect concentration and temperature. This work significantly
advances the current understanding of defect structure/evolution and
structural transitions in 2D TMDs, which is crucial for designing
nanoscale devices with desired functionality
Three-Dimensional Integrated X‑ray Diffraction Imaging of a Native Strain in Multi-Layered WSe<sub>2</sub>
Emerging
two-dimensional (2-D) materials such as transition-metal
dichalcogenides show great promise as viable alternatives for semiconductor
and optoelectronic devices that progress beyond silicon. Performance
variability, reliability, and stochasticity in the measured transport
properties represent some of the major challenges in such devices.
Native strain arising from interfacial effects due to the presence
of a substrate is believed to be a major contributing factor. A full
three-dimensional (3-D) mapping of such native nanoscopic strain over
micron length scales is highly desirable for gaining a fundamental
understanding of interfacial effects but has largely remained elusive.
Here, we employ coherent X-ray diffraction imaging to directly image
and visualize in 3-D the native strain along the (002) direction in
a typical multilayered (∼100–350 layers) 2-D dichalcogenide
material (WSe<sub>2</sub>) on silicon substrate. We observe significant
localized strains of ∼0.2% along the out-of-plane direction.
Experimentally informed continuum models built from X-ray reconstructions
trace the origin of these strains to localized nonuniform contact
with the substrate (accentuated by nanometer scale asperities, i.e.,
surface roughness or contaminants); the mechanically exfoliated stresses
and strains are localized to the contact region with the maximum strain
near surface asperities being more or less independent of the number
of layers. Machine-learned multimillion atomistic models show that
the strain effects gain in prominence as we approach a few- to single-monolayer
limit. First-principles calculations show a significant band gap shift
of up to 125 meV per percent of strain. Finally, we measure the performance
of multiple WSe<sub>2</sub> transistors fabricated on the same flake;
a significant variability in threshold voltage and the “off”
current setting is observed among the various devices, which is attributed
in part to substrate-induced localized strain. Our integrated approach
has broad implications for the direct imaging and quantification of
interfacial effects in devices based on layered materials or heterostructures
Ultrafast Three-Dimensional Integrated Imaging of Strain in Core/Shell Semiconductor/Metal Nanostructures
Visualizing the dynamical
response of material heterointerfaces
is increasingly important for the design of hybrid materials and structures
with tailored properties for use in functional devices. In situ characterization
of nanoscale heterointerfaces such as metal–semiconductor interfaces,
which exhibit a complex interplay between lattice strain, electric
potential, and heat transport at subnanosecond time scales, is particularly
challenging. In this work, we use a laser pump/X-ray probe form of
Bragg coherent diffraction imaging (BCDI) to visualize in three-dimension
the deformation of the core of a model core/shell semiconductor–metal
(ZnO/Ni) nanorod following laser heating of the shell. We observe
a rich interplay of radial, axial, and shear deformation modes acting
at different time scales that are induced by the strain from the Ni
shell. We construct experimentally informed models by directly importing
the reconstructed crystal from the ultrafast experiment into a thermo-electromechanical
continuum model. The model elucidates the origin of the deformation
modes observed experimentally. Our integrated imaging approach represents
an invaluable tool to probe strain dynamics across mixed interfaces
under operando conditions
Ultrafast Three-Dimensional Integrated Imaging of Strain in Core/Shell Semiconductor/Metal Nanostructures
Visualizing the dynamical
response of material heterointerfaces
is increasingly important for the design of hybrid materials and structures
with tailored properties for use in functional devices. In situ characterization
of nanoscale heterointerfaces such as metal–semiconductor interfaces,
which exhibit a complex interplay between lattice strain, electric
potential, and heat transport at subnanosecond time scales, is particularly
challenging. In this work, we use a laser pump/X-ray probe form of
Bragg coherent diffraction imaging (BCDI) to visualize in three-dimension
the deformation of the core of a model core/shell semiconductor–metal
(ZnO/Ni) nanorod following laser heating of the shell. We observe
a rich interplay of radial, axial, and shear deformation modes acting
at different time scales that are induced by the strain from the Ni
shell. We construct experimentally informed models by directly importing
the reconstructed crystal from the ultrafast experiment into a thermo-electromechanical
continuum model. The model elucidates the origin of the deformation
modes observed experimentally. Our integrated imaging approach represents
an invaluable tool to probe strain dynamics across mixed interfaces
under operando conditions
Quantitative Observation of Threshold Defect Behavior in Memristive Devices with <i>Operando</i> X‑ray Microscopy
Memristive
devices are an emerging technology that enables both
rich interdisciplinary science and novel device functionalities, such
as nonvolatile memories and nanoionics-based synaptic electronics.
Recent work has shown that the reproducibility and variability of
the devices depend sensitively on the defect structures created during
electroforming as well as their continued evolution under dynamic
electric fields. However, a fundamental principle guiding the material
design of defect structures is still lacking due to the difficulty
in understanding dynamic defect behavior under different resistance
states. Here, we unravel the existence of threshold behavior by studying
model, single-crystal devices: resistive switching requires that the
pristine oxygen vacancy concentration reside near a critical value.
Theoretical calculations show that the threshold oxygen vacancy concentration
lies at the boundary for both electronic and atomic phase transitions.
Through <i>operando</i>, multimodal X-ray imaging, we show
that field tuning of the local oxygen vacancy concentration below
or above the threshold value is responsible for switching between
different electrical states. These results provide a general strategy
for designing functional defect structures around threshold concentrations
to create dynamic, field-controlled phases for memristive devices