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At least 631 records · Page 35

Elucidating the complex interplay between thermodynamics, kinetics, and electrochemistry in battery electrodes through phase-field modeling

Abstract This article highlights applications of phase-field modeling to electrochemical systems, with a focus on battery electrodes. We first provide an overview on the physical processes involved in electrochemical systems and applications of the phase-field approach to understand the thermodynamic and kinetic mechanisms underlying these processes. We employ two examples to highlight how realistic thermodynamics and kinetics can naturally be incorporated into phase-field modeling of electrochemical processes. One is a composite battery cathode with an intercalation compound (Li x FePO 4 ) as the electrochemically active material, and the other is a displacement reaction compound (Li–Cu–TiS 2 ). With the input parameters mostly from atomistic calculations and experimental measurements, phase-field simulations allowed us to untangle the interactions among transport, reaction, electricity, chemistry, and thermodynamics that lead to highly complex evolution of the materials within battery electrodes. The implications of these observations for battery performance and degradation are discussed. Graphical abstract

Andrews, W. Beck (ORCID:0000000287824621)↗

Functional Photoresists for Energy Applications. Final Report

Monolithic ultralow-density porous bulk materials have recently attracted much interest due to many emerging applications in the areas of catalysis, energy storage and conversion, and thermal insulation. They are also important components of high energy density (HED) and inertial confinement fusion (ICF) targets. However, despite tremendous progress that has been made in the synthesis of porous materials, deterministic and independent control over microscopic architecture, density and composition remain key issues, and their integration in high precision devices requires cost and time-intensive mechanical machining that not only reduces reproducibility by generating debris but also limits the complexity of the 3D shapes that can be realized. In this project, we overcame these limitations by developing a universal templating capability that provides deterministic and independent control over density, composition, architecture, and macroscopic sample shape. This was achieved by developing the technology to 1) 3D print ultrahigh resolution, ultra-high precision polymeric micro-lattice templates, 2) coat these templates with the desired materials, and 3) removing the template (Fig. 1a). Atomic layer deposition (ALD) provides the atomic scale coating thickness accuracy required for precisely controlling density. While this templating approach had been demonstrated in prior work, limitations in suitable photoresists, 3D print technologies, print design, and template removal techniques did not allow the fabrication of millimeter-sized high-precision parts with sub-micron resolution. To enable this technology, we developed 1) two-photon polymerization (TPP) print designs that enable the fabrication of millimeter-sized, mechanically robust polymeric templates with sub-micron resolution and 2) a continuum level TPP printing simulation capability for additional print design guidance; 3) atomistic models to study photoresist polymerization kinetics and network topography, 4) refractive index matched polymeric and preceramic TPP photoresists, and 5) functional TPP photoresists including porous voxel structures and self-immolative polymer photoresist chemistries; and 6) damage free template removal techniques that enable the fabrication of defect-free high-precision low-density foam components. We also developed a templating approach for pure carbon microlattices with a unique tube-in-tube ligament morphology. As a test platform, we pursued the fabrication of foam liners that promise to further increase the neutron yield in indirect drive ICF experiments by improving implosion symmetry control and coupling between the laser and the deuterium-tritium fuel. This application requires fabrication and integration of a ultra-high precision, millimeter-sized, thin-walled (200-400 micrometer thick), low-density (10-30 mg/cc), high atomic number (high Z) cylindrical foam tube into the gold hohlraum of an indirect drive ICF target (Fig. 1b). While our hohlraum liner test case will mainly find application in HED and ICF experiments, the underlying science will also directly apply to previously developed nanoparticle and additive manufacturing technologies and will advance those techniques as well.

36 MATERIALS SCIENCE↗

Relationship between microporous structure and light gas transport through glassy polymeric membranes revealed by molecular simulations

Microporous glassy polymers are attractive materials for gas separation membranes, due to their high permeability and tailorable selectivity, provided physical aging can be delayed. The archetypal microporous glassy polymer, PTMSP, can be blended with a hyper-crosslinked isatin–triptycene porous polymer network (PPN) to delay physical aging. However, while PPN is effective at reducing physical aging, it also affects the permeability of light gases through PTMSP. Molecular dynamics simulations were used here to shed fundamental light on the mechanisms responsible for these effects. Atomistic models are developed that satisfactorily reproduce experimental observations such as matrix density and cavity size distributions for neat PTMSP as well as for PTMSP–PPN blends. Analysis of the simulation results suggests that physical aging is delayed because the PPN inclusions slow down PTMSP relaxation while reducing the connectivity between free volume pockets. To understand how PPN inclusions affect light gas permeability, the atomistic models developed are used to probe CO 2 and CH 4 diffusion and sorption. These simulations are conducted for PTMSP matrices exhibiting varying density, towards reproducing experimental permeability data. Interrogating the simulation trajectories, it is discovered that while CH 4 travels preferentially through the free volume cavities, CO 2 preferentially interacts with the available surfaces, especially in the presence of PPN. These differences help interpret experimental observations. The transport of C 2 H 6 and H 2 S through PTMSP matrices was also investigated. These gases, and in particular H 2 S, were found to absorb within PTMSP, yielding very low diffusion coefficients. The ability to predict differences in diffusion pathways for various natural gas components unveils the possibility of engineering membranes to control permeability and selectivity towards large-scale applications.

Bao Le, Tran Thi [Univ. of Oklahoma, Norman, OK (U↗

A Revisited Mechanism of the Graphite-to-Diamond Transition at High Temperature

The graphite-diamond transition, under high-pressure and high-temperature conditions, has been a central subject in physical science. However, its atomistic mechanism remains under debate. Employing large-scale molecular dynamics (MD) simulations, we report a mechanism whereby the diamond nuclei in the graphite matrix propagate in two preferred directions, among which the graphite [120] is about 2.5 times faster than [001]. Consequently, cubic diamond (CD) is the kinetically favorable product, while only a few hexagonal diamonds (HDs) can exist as the twins of CDs. The coherent interface of t-(100)gr//(11-1)cd + [010]gr//[1-10]cd observed in MD simulation was confirmed by our high-resolution transmission electron microscopy experiment. This proposed mechanism not only clarifies the role of HD in graphite-diamond transition but also yields atomistic insight into strengthening synthetic diamond via microstructure engineering.

36 MATERIALS SCIENCE↗

Fast predictions of liquid-phase acid-catalyzed reaction rates using molecular dynamics simulations and convolutional neural networks

The rates of liquid-phase, acid-catalyzed reactions relevant to the upgrading of biomass into high-value chemicals are highly sensitive to solvent composition and identifying suitable solvent mixtures is theoretically and experimentally challenging. We show that the complex atomistic configurations of reactant–solvent environments generated by classical molecular dynamics simulations can be exploited by 3D convolutional neural networks to enable accurate predictions of Brønsted acid-catalyzed reaction rates for model biomass compounds. We develop a 3D convolutional neural network, which we call SolventNet, and train it to predict acid-catalyzed reaction rates using experimental reaction data and corresponding molecular dynamics simulation data for seven biomass-derived oxygenates in water–cosolvent mixtures. We show that SolventNet can predict reaction rates for additional reactants and solvent systems an order of magnitude faster than prior simulation methods. This combination of machine learning with molecular dynamics enables the rapid, high-throughput screening of solvent systems and identification of improved biomass conversion conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigation of plasmon relaxation mechanisms using nonadiabatic molecular dynamics

Hot carriers generated from the decay of plasmon excitation can be harvested to drive a wide range of physical or chemical processes. However, their generation efficiency is limited by the concomitant phonon-induced relaxation processes by which the energy in excited carriers is transformed into heat. However, simulations of dynamics of nanoscale clusters are challenging due to the computational complexity involved. Here, in this paper, we adopt our newly developed Trajectory Surface Hopping (TSH) nonadiabatic molecular dynamics algorithm to simulate plasmon relaxation in Au 20 clusters, taking the atomistic details into account. The electronic properties are treated within the Linear Response Time-Dependent Tight-binding Density Functional Theory (LR-TDDFTB) framework. The relaxation of plasmon due to coupling to phonon modes in Au 20 beyond the Born–Oppenheimer approximation is described by the TSH algorithm. The numerically efficient LR-TDDFTB method allows us to address a dense manifold of excited states to ensure the inclusion of plasmon excitation. Starting from the photoexcited plasmon states in Au 20 cluster, we find that the time constant for relaxation from plasmon excited states to the lowest excited states is about 2.7 ps, mainly resulting from a stepwise decay process caused by low-frequency phonons of the Au 20 cluster. Furthermore, our simulations show that the lifetime of the phonon-induced plasmon dephasing process is ~10.4 fs and that such a swift process can be attributed to the strong nonadiabatic effect in small clusters. Our simulations demonstrate a detailed description of the dynamic processes in nanoclusters, including plasmon excitation, hot carrier generation from plasmon excitation dephasing, and the subsequent phonon-induced relaxation process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atomistic insights into the heat conductance across the interfaces between erythritol and different metals: A non-equilibrium molecular dynamics study

The heat conductance across the interface between a phase change material (PCM) and the metal shell is important for thermal design of latent heat storage systems. Non-equilibrium molecular dynamics simulations were carried out in this work to unravel, at the atomistic level, the interfacial heat conductance mechanisms between erythritol (the most promising medium-temperature polyol PCM) and two different metals (i.e., copper and aluminum). The interfacial contact ratio was introduced as a parameter to represent different contact conditions at the interfaces, for example, different surface roughness levels of the metals. It was found that with the increase of interfacial contact ratio, the temperature difference between the erythritol/metal interfaces decreases, whereas the interfacial heat transfer coefficient increases gradually. At the perfect contact condition, i.e., the interfacial contact ratio reaches 100%, the interfacial heat transfer coefficients across the erythritol/Cu and erythritol/Al interfaces were predicted to be 398 ± 26 MW/m 2 K and 544 ± 11 MW/m 2 K, respectively. The interfacial heat conductance of erythritol/Al is better than that of erythritol/Cu. The mismatch of atomic spectral density across the interfaces between erythritol and the two metals was analyzed and distinguished. These results could guide the selection of packaging materials and the thermal design of erythritol-based latent heat storage systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Atomistic Materials Modeling of High-Pressure Hydrogen Interactions in Ethylene Propylene Diene Monomer (EPDM) Rubber

Elastomeric rubbers serve a vital role as sealing materials in the hydrogen storage and transport infrastructure. With applications including O-rings and hose-liners, these components are exposed to pressurized hydrogen at a range of temperatures, cycling rates, and pressure extremes. Cyclic (de)pressurization is known to degrade these materials through the process of cavitation. This readily visible failure mode occurs as a fracture or rupture of the material and is due to the oversaturated gas localizing to form gas bubbles. Computational modeling in the Hydrogen Materials Compatibility Program (H-Mat), co-led by Sandia National Laboratories and Pacific Northwest National Laboratory, employs multi-scale simulation efforts to build a predictive understanding of hydrogen-induced damage in materials. Modeling efforts within the project aim to provide insight into how to formulate materials that are less sensitive to high-pressure hydrogen-induced failure. In this document, we summarize results from atomistic molecular dynamics simulations, which make predictive assessments of the effects of compositional variations in the commonly used elastomer, ethylene propylene diene monomer (EPDM).

08 HYDROGEN↗

A Multiscale Simulation Study of Influence of Morphology on Ion Transport in Block Copolymeric Ionic Liquids

In this work, we present results of a multiscale simulation study involving coarse-graining and reverse-mapping steps probing at an atomistic resolution the influence of morphology on ion transport in block copolymer polymeric ionic liquids. We provide a detailed description of the multiscale simulation methodology and then describe the results in the context of four microphase-separated morphologies: two lamella systems, a cylinder, and a gyroid morphology. For the framework adopted in this study (in which the total number of ions was maintained fixed), morphology had little influence on the fraction of ions segregating to the interface and the coordination and hopping characteristics of such interfacially present ions. Such results manifested in anion mobilities being insensitive to the morphology once the dimensionality of the morphology was accounted for. Overall, our results are consistent with the hypothesis that the mobility of ions in such microphase-separated morphologies, after accounting for the dimensionality effects, can be roughly correlated to a linear superposition based on the fraction of bulk anions, which possess mobilities unperturbed from their values in the conducting homopolymers, and the interfacial anions, which exhibit much lower mobilities.

36 MATERIALS SCIENCE↗

Distance-dependent dielectric constant at the calcite/electrolyte interface: Implication for surface complexation modeling

Hypothesis: The electrical double layer formed at the mineral/electrolyte interface is often modeled using mean-field approaches based on a continuum description of the solvent whose dielectric constant is assumed to decrease monotonically with decreasing distance to the surface. In contrast, molecular simulations show that the solvent polarizability oscillates near the surface similar to the water density profile - as shown previously, for example, by Bonthuis et al. (D.J. Bonthuis, S. Gekle, R.R. Netz, Dielectric Profile of Interfacial Water and its Effect on Double-Layer Capacitance, Phys Rev Lett 107(16) (2011) 166102). Here, we showed that molecular and mesoscale pictures agree by spatially averaging the dielectric constant obtained from molecular dynamics simulations over the distances relevant to the mean-field representation. In addition, the values of capacitances used to describe the electrical double layer in Surface Complexation Models (SCMs) of the mineral/electrolyte interface can be estimated using molecularly informed spatially averaged dielectric constants and positions of hydration layers. Experiments: First, we used molecular dynamics simulations to model the calcite 101¯4/electrolyte interface. Next, by using atomistic trajectories, we calculated the distance-dependent static dielectric constant and water density in the direction normal to the. Finally, we applied spatial compartmentalization consistent with the model of parallel-plate capacitors connected in series to estimate SCM capacitances. Findings: Computationally expensive simulations are required to determine the dielectric constant profile of interfacial water near the mineral surface. On the other hand, water density profiles are readily assessable from much shorter simulation trajectories. Our simulations confirmed that dielectric and water density oscillations at the interface are correlated. Here, we parametrized linear regression models to estimate the dielectric constant directly from the local water density. This is a significant computational shortcut compared to slowly converging calculations relying on total dipole moment fluctuations. The amplitude of the interfacial dielectric constant oscillation can exceed the dielectric constant of the bulk water, suggesting an ice-like frozen state, but only if there are no electrolyte ions. The interfacial accumulation of electrolyte ions causes a decrease in the dielectric constant due to the reduction of water density and re-orientation of water dipoles in ion hydration shells. Finally, we show how to use the computed dielectric properties to estimate SCM's capacitances.

58 GEOSCIENCES↗

Molecular‐Level Insight into the Chlorofluorocarbons Adsorption by Defective Covalent Organic Polymers

Abstract Halocarbons have important industrial applications, but because of their contribution to global warming and the fact that they can cause ozone depletion, they are considered highly toxic. Hence, the techniques that can capture and recover the used halocarbons with energy‐efficient methods have been recently received greater attention. In this contribution, we report the capture of dichlorodifluoromethane (R12), which has high global warming and ozone depletion potential, using covalent organic polymers (COPs). The defect‐engineered COPs were synthesized and demonstrated outstanding sorption capacities, ~226 wt % of R12 combined with linear‐shaped adsorption isotherms. We further identified the plausible microscopic adsorption mechanism of the investigated COPs via grand canonical Monte Carlo simulations applied to non‐defective and a collection of atomistic models of the defective COPs. The modeling work suggests that significant R12 adsorption performance is attributed to a gradual increment of porosities due to isolated/interconnected micro‐/meso‐pore channels and the change of the long‐range ordering of both COPs. The successive hierarchical‐pore‐filling mechanism promotes R12 molecular adsorption via moderate van der Waals adsorbate‐adsorbent interactions in the micropores of both COPs at low pressure followed by adsorbate‐adsorbate interactions in the extra‐voids created at moderate to high pressure ranges. This continuous pore‐filling mechanism makes defective COPs as promising sorbents for halocarbon adsorption.

Shen, Jian↗

Understanding Adsorption and Reactions at Aqueous Oxide Interfaces with Neural Network Potential Molecular Dynamics

Chemical processes at metal oxide−water interfaces are of central importance in geochemistry, biology, and energy technologies. A better understanding of these processes would allow us to make a significant step toward optimizing and controlling them, which could in turn lead to broader impacts. Computational modeling is indispensable to accomplishing this task because complexity and disorder often make it difficult to extract atomistic information from experiments. Balancing computational cost and accuracy, simulation schemes based on efficient machine learning representations of the potential energy surface (PES) predicted by ab initio calculations have become increasingly popular over the past decade. In particular, several studies have demonstrated the ability of machine learning models to accurately reproduce the complex ab initio PESs of aqueous oxide interfaces, allowing simulations of systems and processes that are not accessible with ab initio methods. In this Account, we review our recent efforts to understand adsorption processes and reactions at aqueous oxide interfaces using deep potential molecular dynamics (DPMD), a simulation scheme employing deep neural networks (DNNs), which has proven to be quite successful in accurately describing many different systems in the condensed phase. After summarizing the DPMD methodology, we first review our work on the acid−base chemistry of oxide surfaces in contact with water, a fundamental characteristic that controls proton transfer and surface charge at the interface. We focus on the aqueous interface of rutile IrO 2 , an oxide material thus far considered the best catalyst for the oxygen evolution reaction (OER). We show that this interface is characterized by a large fraction of dissociated water and a strong Brønsted acidity of the surface sites, in good agreement with the experimentally measured value of the point of zero proton charge. In our second example, we investigate how the adsorption of organic species from ambient air or water affects the structure and wettability of the aqueous interfaces of TiO 2 , a prototypical photocatalytic material. This is a question that is relevant to understanding the UV-induced hydrophilicity of TiO 2 surfaces, a property at the basis of self-cleaning windows and related applications. Specifically focusing on formic and acetic acids, the two most common atmospheric organic acids, our simulations reveal that these acids control the wettability of TiO 2 largely through acid−base chemistry at the interface rather than chemisorption on the oxide surface, a finding that could help improve the design of self-cleaning surfaces and photocatalytic devices. Finally, we review our recent study of methanol at TiO 2 −water interfaces, a system whose interest is largely motivated by the role of methanol in enhancing photocatalytic hydrogen evolution on TiO 2 . Our simulations provide mechanistic insights into the coupled roles of the organic adsorbate and water at the TiO 2 interface, with implications for how methanol enhances the activity of H 2 evolution.

adsorption↗

Nonadiabatic Force Matching for Alchemical Free-Energy Estimation

We propose a method to compute free-energy differences from nonadiabatic alchemical transformations by using flow-based generative models. The method, nonadiabatic force matching, hinges on estimating the dissipation along an alchemical switching process in terms of a nonadiabatic force field that can be learned through stochastic flow matching. The learned field can be used in conjunction with short-time trajectory data to evaluate upper and lower bounds on the alchemical free energy that variationally converge to the exact value if the field is optimal. Applying the method to evaluate the alchemical free energy of atomistic models shows that it can substantially reduce the simulation cost of a free-energy estimate at a negligible loss of accuracy when compared with thermodynamic integration.

Computational chemistry↗

Helium bubble size effects on the surface morphological response of plasma-facing tungsten

Abstract We report a simulation study on the effects of helium (He) bubble size on the morphological evolution and pattern formation on the surface of tungsten used as a plasma-facing component (PFC) in nuclear fusion devices. We have carried out a systematic investigation based on self-consistent dynamical simulations of surface morphological evolution according to an atomistically-informed, 3D continuum-scale model that captures well the relevant length and time scales of surface nanostructure formation in PFC tungsten. The model accounts for PFC surface diffusion, driven by the biaxial compressive stress originating from the over-pressurized He bubbles in the near-surface region of PFC tungsten as a result of He plasma exposure, combined with the formation of self-interstitial atoms in tungsten that diffuse toward the PFC surface and the flux of surface adatoms generated as a result of surface vacancy-adatom pair formation upon He implantation; this transport of surface adatoms contributes to the anisotropic growth of surface nanostructural features due to the different rates of adatom diffusion along and across step edges of islands on the tungsten surface. Our detailed analysis reveals that varying the average He bubble size plays an important role in the PFC surface growth kinetics as well as the resulting surface topography. Specifically, we find that an increase in the He bubble size leads to a deceleration in the growth rate of the tungsten nanotendrils that emanate from the PFC surface. We also find that the separation distance between the resulting surface features increases with increasing He bubble size, as well as over time. This coarsening effect is a thermally activated process resulting in an accurate description of the temperature dependence of the average surface feature separation by an Arrhenius relation.

36 MATERIALS SCIENCE↗

Thickness and strain dependence of piezoelectric coefficient in BaTiO 3 thin films

We explore the thickness dependence of the converse piezoelectric coefficient (d 33 ) in epitaxial thin films of BaTiO 3 (BTO) grown on (001) SrTiO 3 substrates. Piezoresponse force microscope was performed using an atomic force microscope equipped with an interferometric displacement sensor allowing direct quantification of electromechanical coupling coefficients in BTO free from unwanted background contributions. We find that 80-nm-thick films exhibit a d 33 of ~20.5pm/V, but as the thickness is reduced, the d 33 reduces to less than 2 pm/V for a 10 nm film. To explain the atomistic origin of the effect, we performed molecular dynamics simulations with a recently developed ab initio-derived reactive force field, constructed using the ReaxFF framework. Simulations predict that under applied electric fields thin films of BaTiO 3 show an increasing thickness, with compressive strain, of the region screening the depolarization-field. This study confirms quantitatively the drop in piezoelectric performance in BTO ultrathin films and again highlights the importance of the screening mechanisms when films approach the ultrathin limits in dictating the functional behaviors.

36 MATERIALS SCIENCE↗

Circumventing the phonon bottleneck by multiphonon-mediated hot exciton cooling at the nanoscale

Abstract Nonradiative processes govern efficiencies of semiconductor nanocrystal (NC)-based devices. A central process is hot exciton cooling, or the nonradiative relaxation of a highly excited electron/hole pair to form a band-edge exciton. Due to quantum confinement effects, the timescale and mechanism of cooling are not well understood. A mismatch between electronic energy gaps and phonon frequencies has led to the hypothesis of a phonon bottleneck and extremely slow cooling, while enhanced electron-hole interactions have suggested ultrafast cooling. Experimental measurements of the cooling timescale range six orders of magnitude. Here, we develop an atomistic approach to describe phonon-mediated exciton dynamics and simulate cooling in NCs of experimentally relevant sizes. We find that cooling occurs on ~30 fs timescales in CdSe NCs, in agreement with the most recent measurements, and that the phonon bottleneck is circumvented through a cascade of multiphonon-mediated relaxation events. Furthermore, we identify NC handles for tuning the cooling timescale.

36 MATERIALS SCIENCE↗

Atomistic observation on diffusion-mediated friction between single-asperity contacts

Super-lubricity, a sliding regime in which friction almost vanishes, has been well-documented with the advent of atomic force microscopy (AFM) and molecular dynamics (MD) simulation due to its enormous implications for manufacturing micro-/nano-electromechanical systems (MEMS/NEMS). Nevertheless, the atomistic mechanisms for super-lubricious behaviors are still elusive, primarily due to a lack of direct observation of interface at atomic resolution during frictional process. Here by using in situ high-resolution transmission electron microscopy (HRTEM) coupled with AFM, we report diffusion-mediated formation of a loosely-packed interfacial layer between two metallic asperities at infinitesimal normal forces, which is responsible for the sliding regime, super-lubricity exhibiting ultra-low friction forces and continuous sliding. By contrast, the loosely-packed interfacial layer vanishes along with the super-lubricity, leading to typical stick-slip friction. Additionally, in situ TEM observation and MD simulations reveals the crucial role that atom diffusion plays in atomic friction, and provides new insights into the fundamental mechanisms of super-lubricity.

42 ENGINEERING↗

Strain release by 3D atomic misfit in fivefold twinned icosahedral nanoparticles with amorphization and dislocations

Multiple twinning to form fivefold twinned nanoparticles in crystal growth is common and has attracted broad attention ranging from crystallography research to physical chemistry and materials science. Lattice-misfit strain and defects in multiple twinned nanoparticles (MTP) are key to understand and tailor their electronic properties. However, the structural defects and related strain distributions in MTPs are poorly understood in three dimensions (3D). Here, we show the 3D atomic misfit and strain relief mechanism in fivefold twinned icosahedral nanoparticles with amorphization and dislocations by using atomic resolution electron tomography. We discover a two-sided heterogeneity in variety of structural characteristics. A nearly ideal crystallographic fivefold face is always found opposite to a less ordered face, forming Janus-like icosahedral nanoparticles with two distinct hemispheres. The disordered amorphous domains release a large amount of strain. Molecular dynamics simulations further reveal the Janus-like icosahedral nanoparticles are prevalent in the MTPs formed in liquid-solid phase transition. This work provides insights on the atomistic models for the modelling of formation mechanisms of fivefold twinned structures and computational simulations of lattice distortions and defects. We anticipate it will inspire future studies on fundamental problems such as twin boundary migration and kinetics of structures in 3D at atomic level.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗