Internal Structure of Incipient Soot from Acetylene Pyrolysis Obtained via Molecular Dynamics Simulations.

A series of reactive molecular dynamics simulations is used to study the internal structure of incipient soot particles obtained from acetylene pyrolysis. The simulations were performed using the ReaxFF potential at four different temperatures. The resulting soot particles are cataloged and analyzed to obtain statistics of their mass, volume, density, C/H ratio, number of cyclic structures, and other features. A total of 3324 incipient soot particles were analyzed in this study. Based on their structural characteristics, the incipient soot particles are classified into two classes, termed type 1 and type 2 incipient soot particles in this work. The radial distribution of density, cyclic (5-, 6-, or 7-member rings) structures, and C/H ratio inside the particles revealed a clear difference in the internal structure between type 1 and type 2 particles. These classes were further found to be well represented by the size of the particles, with smaller particles in type 1 and larger particles in type 2. The radial distributions of ring structures, density, and the C/H ratio indicated the presence of a dense core region in type 2 particles. In contrast, no clear evidence of the presence of a core was found in type 1 particles. In type 2 incipient soot particles, the boundary between the core and shell was found to be around 50-60% of the particle's radius of gyration.

Aggregation and breakage dynamics of alumina particles under shear by coupled Computational Fluid Dynamics - Discrete Element Method.

HYPOTHESIS: Shear affects simultaneous aggregation and fragmentation of fine particles. Understanding the effect of shear on the dynamics of particle aggregation and break-up is important to predict aggregate size and structure. It is hypothesized that there is a transition from pure breakage of large aggregates to regimes where restructuring and aggregation also play a role as aggregates become smaller. SIMULATIONS: Here, aggregation and fragmentation dynamics of alumina particles are investigated under laminar shear flow using Discrete Element Method (DEM) coupled with Computational Fluid Dynamics (CFD). The effect of the shear rate on the aggregation and breakage rates is quantified accounting for particle-particle and particle-fluid interactions. FINDINGS: High shear rates promote the formation of small, compact aggregates. The collision efficiency decreases with increasing shear rate following a power law for shear rates higher than 1250 s-1. The transition from the pure breakage limit to the region dominated by breakage and restructuring has been observed for the first time. The breakage rate decreases significantly as the transition occurs upon decreasing aggregate size. CFD-DEM-derived collision efficiency and breakage rate equations are proposed that can be readily employed in detailed population balance equation models for industrial particle process design.

Particle Engineering via Supramolecular Assembly of Macroscopic Hydrophobic Building Blocks.

Tailoring the hydrophobicity of supramolecular assembly building blocks enables the fabrication of well-defined functional materials. However, the selection of building blocks used in the assembly of metal-phenolic networks (MPNs), an emerging supramolecular assembly platform for particle engineering, has been essentially limited to hydrophilic molecules. Herein, we synthesized and applied biscatechol-functionalized hydrophobic polymers (poly(methyl acrylate) (PMA) and poly(butyl acrylate) (PBA)) as building blocks to engineer MPN particle systems (particles and capsules). Our method allowed control over the shell thickness (e.g., between 10 and 21 nm), stiffness (e.g., from 10 to 126 mN m-1 ), and permeability (e.g., 28-72 % capsules were permeable to 500 kDa fluorescein isothiocyanate-dextran) of the MPN capsules by selection of the hydrophobic polymer building blocks (PMA or PBA) and by controlling the polymer concentration in the MPN assembly solution (0.25-2.0 mM) without additional/engineered assembly processes. Molecular dynamics simulations provided insights into the structural states of the hydrophobic building blocks during assembly and mechanism of film formation. Furthermore, the hydrophobic MPNs facilitated the preparation of fluorescent-labeled and bioactive capsules through postfunctionalization and also particle-cell association engineering by controlling the hydrophobicity of the building blocks. Engineering MPN particle systems via building block hydrophobicity is expected to expand their use.

Silicon-Based Anodes for Li Batteries: Thermodynamics, Structural Analysis, and Li Diffusion.

Quantum mechanical and machine learning models are used to analyze the properties of silicon composite materials and their impact on anode performance. The analysis focuses on addressing challenges related to significant volume expansion during lithiation and provides valuable insights into the Gibbs free energy, chemical potentials, and relative stability of Li0 and Li+ species. Furthermore, the study explores how Li+ ions behave in the primary and secondary phases of the anode, assessing the impact of their formation on ion diffusion. This work highlights the fundamental significance of secondary phases in shaping microstructural features that impact anode properties, elucidating their contribution to the Li diffusion pathway tortuosity, which is the primary cause of the fracture of Si anodes in Li-ion batteries.

Nucleation Rate of N2 and O2 in Cryogenic H2 and He.

The homogeneous nucleation of N2 and O2 in cryogenic H2 and He is investigated by using classical molecular dynamics (MD) simulations. The nucleation kinetics of N2 and O2 clusters, including nucleation rate, critical cluster size, and cluster energy, are elucidated in H2 and He carrier gas at thermalization temperatures of 30-80 K and initial gas densities of 5.65 × 1024-2 × 1027 m-3. The energy released from the clusters during nucleation increases the system temperature by 77-138%, consistent with N2 nucleation experiments in supersonic nozzles and the mean-field kinetic nucleation theory. The nucleation rate derived by MD, Jsim, spans across 2.14 × 1029-5.25 × 1036 m-3 s-1 for both N2 and O2 under all conditions. The MD-obtained homogeneous nucleation rate is in agreement with predictions from the self-consistent classical nucleation theory (CNT) at low temperature (<70 K) but is 3-7 orders of magnitude faster than the CNT when temperature exceeds 70 K, consistent with the literature. Increasing temperature and decreasing concentration of the nucleating vapors leads to larger critical cluster sizes. The CNT underpredicts the critical cluster size at cryogenic temperatures below 60 K by 200-700%. The present MD methodology can be used for the direct determination of the nucleation rate and critical cluster size of N2 and O2 under cryogenic conditions, circumventing the assumptions inherent in CNT.

Exploiting Molecular Dynamics in Composite Coatings to Design Robust Super-Repellent Surfaces.

Fluorinated motifs are promising for the engineering of repellent coatings, however, a fundamental understanding of how to effectively bind these motifs to various substrates is required to improve their stability in different use scenarios. Herein, the binding of fluorinated polyhedral oligomeric silsesquioxanes (POSS) using a cyanoacrylate glue (binder) is computationally and experimentally evaluated. The composite POSS-binder coatings display ultralow surface energy (≈10 mJ m-2 ), while still having large surface adhesions to substrates (300-400 nN), highlighting that super-repellent coatings (contact angles >150°) can be readily generated with this composite approach. Importantly, the coatings show super-repellency to both corrosive liquids (e.g., 98 wt% H2 SO4 ) and ultralow surface tension liquids (e.g., alcohols), with ultralow roll-off angles (<5°), and tunable resistance to liquid penetration. Additionally, these coatings demonstrate the potential in effective cargo loading and robust self-cleaning properties, where experimental datasets are correlated with both relevant theoretical predictions and systematic all-atom molecular dynamics simulations of the repellent coatings. This work not only holds promise for chemical shielding, heat transfer, and liquid manipulations but offers a facile yet robust pathway for engineering advanced coatings by effectively combining components for their mutually desired properties.

Interfacial piezoelectric polarization locking in printable Ti3C2Tx MXene-fluoropolymer composites.

Piezoelectric fluoropolymers convert mechanical energy to electricity and are ideal for sustainably providing power to electronic devices. To convert mechanical energy, a net polarization must be induced in the fluoropolymer, which is currently achieved via an energy-intensive electrical poling process. Eliminating this process will enable the low-energy production of efficient energy harvesters. Here, by combining molecular dynamics simulations, piezoresponse force microscopy, and electrodynamic measurements, we reveal a hitherto unseen polarization locking phenomena of poly(vinylidene fluoride-co-trifluoroethylene) (PVDF-TrFE) perpendicular to the basal plane of two-dimensional (2D) Ti3C2Tx MXene nanosheets. This polarization locking, driven by strong electrostatic interactions enabled exceptional energy harvesting performance, with a measured piezoelectric charge coefficient, d33, of -52.0 picocoulombs per newton, significantly higher than electrically poled PVDF-TrFE (approximately -38 picocoulombs per newton). This study provides a new fundamental and low-energy input mechanism of poling fluoropolymers, which enables new levels of performance in electromechanical technologies.

Exploiting Supramolecular Dynamics in Metal-Phenolic Networks to Generate Metal-Oxide and Metal-Carbon Networks.

Supramolecular complexation is a powerful strategy for engineering materials in bulk and at interfaces. Metal-phenolic networks (MPNs), which are assembled through supramolecular complexes, have emerged as suitable candidates for surface and particle engineering owing to their diverse properties. Herein, we examine the supramolecular dynamics of MPNs during thermal transformation processes. Changes in the local supramolecular network including enlarged pores, ordered aromatic packing, and metal relocation arise from thermal treatment in air or an inert atmosphere, enabling the engineering of metal-oxide networks (MONs) and metal-carbon networks, respectively. Furthermore, by integrating photo-responsive motifs (i.e., TiO2 ) and silanization, the MONs are endowed with reversible superhydrophobic (>150°) and superhydrophilic (≈0°) properties. By highlighting the thermodynamics of MPNs and their transformation into diverse materials, this work offers a versatile pathway for advanced materials engineering.

Modular Assembly of Host-Guest Metal-Phenolic Networks Using Macrocyclic Building Blocks.

The manipulation of interfacial properties has broad implications for the development of high-performance coatings. Metal-phenolic networks (MPNs) are an emerging class of responsive, adherent materials. Herein, host-guest chemistry is integrated with MPNs to modulate their surface chemistry and interfacial properties. Macrocyclic cyclodextrins (host) are conjugated to catechol or galloyl groups and subsequently used as components for the assembly of functional MPNs. The assembled cyclodextrin-based MPNs are highly permeable (even to high molecular weight polymers: 250-500 kDa), yet they specifically and noncovalently interact with various functional guests (including small molecules, polymers, and carbon nanomaterials), allowing for modular and reversible control over interfacial properties. Specifically, by using either hydrophobic or hydrophilic guest molecules, the wettability of the MPNs can be readily tuned between superrepellency (>150°) and superwetting (ca. 0°).

Condensation and dissociation rates for gas phase metal clusters from molecular dynamics trajectory calculations.

In gas phase synthesis systems, clusters form and grow via condensation, in which a monomer binds to an existing cluster. While a hard-sphere equation is frequently used to predict the condensation rate coefficient, this equation neglects the influences of potential interactions and cluster internal energy on the condensation process. Here, we present a collision rate theory-molecular dynamics simulation approach to calculate condensation probabilities and condensation rate coefficients. We use this approach to examine atomic condensation onto 6-56-atom Au and Mg clusters. The probability of condensation depends upon the initial relative velocity (v) between atom and cluster and the initial impact parameter (b). In all cases, there is a well-defined region of b-v space where condensation is highly probable, and outside of which the condensation probability drops to zero. For Au clusters with more than 10 atoms, we find that at gas temperatures in the 300-1200 K range, the condensation rate coefficient exceeds the hard-sphere rate coefficient by a factor of 1.5-2.0. Conversely, for Au clusters with 10 or fewer atoms and for 14- and 28-atom Mg clusters, as cluster equilibration temperature increases, the condensation rate coefficient drops to values below the hard-sphere rate coefficient. Calculations also yield the self-dissociation rate coefficient, which is found to vary considerably with gas temperature. Finally, calculations results reveal that grazing (high b) atom-cluster collisions at elevated velocity (>1000 m s-1) can result in the colliding atom rebounding (bounce) from the cluster surface or binding while another atom dissociates (replacement). The presented method can be applied in developing rate equations to predict material formation and growth rates in vapor phase systems.

Mobility and settling rate of agglomerates of polydisperse nanoparticles.

Agglomerate settling impacts nanotoxicology and nanomedicine as well as the stability of engineered nanofluids. Here, the mobility of nanostructured fractal-like SiO2 agglomerates in water is investigated and their settling rate in infinitely dilute suspensions is calculated by a Brownian dynamics algorithm tracking the agglomerate translational and rotational motion. The corresponding friction matrices are obtained using the HYDRO++ algorithm [J. G. de la Torre, G. del Rio Echenique, and A. Ortega, J. Phys. Chem. B 111, 955 (2007)] from the Kirkwood-Riseman theory accounting for hydrodynamic interactions of primary particles (PPs) through the Rotne-Prager-Yamakawa tensor, properly modified for polydisperse PPs. Agglomerates are generated by an event-driven method and have constant mass fractal dimension but varying PP size distribution, mass, and relative shape anisotropy. The calculated diffusion coefficient from HYDRO++ is used to obtain the agglomerate mobility diameter dm and is compared with that from scaling laws for fractal-like agglomerates. The ratio dm/dg of the mobility diameter to the gyration diameter of the agglomerate decreases with increasing relative shape anisotropy. For constant dm and mean dp, the agglomerate settling rate, us, increases with increasing PP geometric standard deviation σp,g (polydispersity). A linear relationship between us and agglomerate mass to dm ratio, m/dm, is revealed and attributed to the fast Brownian rotation of such small and light nanoparticle agglomerates. An analytical expression for the us of agglomerates consisting of polydisperse PPs is then derived, us=1-ρfρpg3πµmdm (ρf is the density of the fluid, ρp is the density of PPs, µ is the viscosity of the fluid, and g is the acceleration of gravity), valid for agglomerates for which the characteristic rotational time is considerably shorter than their settling time. Our calculations demonstrate that the commonly made assumption of monodisperse PPs underestimates us by a fraction depending on σp,g and agglomerate mass mobility exponent. Simulations are in excellent agreement with deposition rate measurements of fumed SiO2 agglomerates in water.

Surface Composition and Crystallinity of Coalescing Silver-Gold Nanoparticles.

Bimetallic nanoparticles exhibit catalytic, optical, electronic, and magnetic synergy between their constituent metals. Typically, that synergy is traced to the domain structure and surface characteristics of such particles. Here these characteristics of coalescing Ag-Au nanoparticles of various initial sizes and morphologies (segregated or alloys) are investigated by atomistic molecular dynamics (MD) at different temperatures. Silver atoms exhibit increased mobility over Au and occupy gradually the surface of the coalesced (or sintered) bimetallic particle, consistent with scanning electron microscopy and selective O2 chemisorption experiments for heterogeneous catalysis of ethylene oxidation. The characteristic sintering time of equally sized Ag-Au nanoparticles is similar to that of pure Au but shorter than that of Ag nanoparticles. When the latter coalesce with substantially bigger Au ones, a patchy Ag layer is formed at the Au particle surface. However, when Ag nanoparticles are bigger, then Au is rather embedded into Ag, consistent with microscopy data. Most notably, X-ray diffraction (XRD) patterns of Ag-Au nanoparticles are obtained by MD, distinguishing segregated from alloyed ones. The latter exhibit a weaker XRD reflection of the (200) crystalline plane and, most distinctly, form smaller crystal size (highly polycrystalline) than coalescing pure and segregated Ag and Au nanoparticles, quantitatively explaining the structure of flame-made Ag-Au nanoparticles for biomaterial applications.

Coagulation-agglomeration of fractal-like particles: structure and self-preserving size distribution.

Agglomeration occurs in environmental and industrial processes, especially at low temperatures where particle sintering or coalescence is rather slow. Here, the growth and structure of particles undergoing agglomeration (coagulation in the absence of coalescence, condensation, or surface growth) are investigated from the free molecular to the continuum regime by discrete element modeling (DEM). Particles coagulating in the free molecular regime follow ballistic trajectories described by an event-driven method, whereas in the near-continuum (gas-slip) and continuum regimes, Langevin dynamics describe their diffusive motion. Agglomerates containing about 10-30 primary particles, on the average, attain their asymptotic fractal dimension, D(f), of 1.91 or 1.78 by ballistic or diffusion-limited cluster-cluster agglomeration, corresponding to coagulation in the free molecular or continuum regimes, respectively. A correlation is proposed for the asymptotic evolution of agglomerate D(f) as a function of the average number of constituent primary particles, n̅(p). Agglomerates exhibit considerably broader self-preserving size distribution (SPSD) by coagulation than spherical particles: the number-based geometric standard deviations of the SPSD agglomerate radius of gyration in the free molecular and continuum regimes are 2.27 and 1.95, respectively, compared to ∼1.45 for spheres. In the transition regime, agglomerates exhibit a quasi-SPSD whose geometric standard deviation passes through a minimum at Knudsen number Kn ≈ 0.2. In contrast, the asymptotic D(f) shifts linearly from 1.91 in the free molecular regime to 1.78 in the continuum regime. Population balance models using the radius of gyration as collision radius underestimate (up to about 80%) the small tail of the SPSD and slightly overpredict the overall agglomerate coagulation rate, as they do not account for cluster interpenetration during coagulation. In the continuum regime, when a recently developed agglomeration rate is used in population balance equations, the resulting SPSD is in excellent agreement with that obtained by DEM.