Tuning Morphology and Electronics of Aryl moieties for Molecular Applications.
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Holzmann, Michael Josef [Sandia National Laborator↗
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Results for “Morphological”
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Hierarchical reconstruction of 3D well-connected porous media from 2D exemplars using statistics-informed neural network
The relationships between porous microstructures and transport properties are of fundamental importance in various scientific and engineering applications. Due to the intricacy, stochasticity and heterogeneity of porous media, reliable characterization and modeling of transport properties often require a complete dataset of internal microstructure samples. However, it is often an unbearable cost to acquire sufficient 3D digital microstructures by purely using microscopic imaging systems. Herein this paper presents a machine learning-based technique to hierarchically reconstruct 3D well-connected porous microstructures from one isotropic or several anisotropic low-cost 2D exemplar(s). To compactly characterize the large-scale microstructural features, a Gaussian image pyramid is built for each 2D exemplar. Local morphology patterns are collected from the Gaussian image pyramids, and then they serve as the training data to embed the 2D morphological statistics into feed-forward neural networks at multiple length levels. By using a specially-developed morphology integration scheme, the 3D morphological statistics at different levels can be inferred from the statistics-informed neural networks. Gibbs sampling is adopted to hierarchically reconstruct 3D microstructures by using multi-level 3D morphological statistics, where the large-scale, regional and local morphological patterns are statistically generated and successively added to the same 3D random field. The proposed method is tested on a series of porous media with distinct morphologies, and the statistical equivalence between the reconstructed and the real microstructures is systematically evaluated by comparing morphological descriptors and transport properties. The results demonstrate that the proposed 2D-to-3D microstructure reconstruction method is a universal and efficient approach to generating morphologically and physically realistic samples of porous media.
42 ENGINEERING↗
The Importance of Nonequilibrium to Equilibrium Transition Pathways for the Efficiency and Stability of Organic Solar Cells
Controlled morphology of solution-processed thin films have realized impressive achievements for non-fullerene acceptor (NFA)–based organic solar cells (OSCs). Given the large set of donor–acceptor pairs, employing various processing conditions to realize optimal morphology for high efficiency and stable OSCs is a strenuous task. Therefore, comprehensive correlations between processing conditions and morphology evolution pathways have to be developed for efficient performance and stability of devices. Within the framework of the blend system, crystallization transitions of NFA molecules are tracked utilizing the first heating scan of differential scanning calorimeter (DSC) measurement correlating with respective morphology evolution of blend films. Real-time dynamics measurements and morphology characterizations are combined to provide optimal morphology transition pathways as NFA molecules are shown to be released from the mixed phase to form balanced ordered packing with variant processing conditions. Polymer:NFA films are fabricated using blade coating incorporating solvent additive or thermal annealing as processing conditions as a correlation is formulated between performance and stability of solar cells with morphology transition pathways. In conclusion, this work demonstrates the significance of processing condition-controlled transition pathways for the realization of optimal morphology leading to superior OSC devices.
14 SOLAR ENERGY↗
Shape-preserving amorphous-to-crystalline transformation of CaCO3 revealed by in situ TEM
Organisms use inorganic ions and macromolecules to regulate crystallization from amorphous- precursors, endowing natural biominerals with complex morphologies and enhanced properties. The mechanisms by which modifiers enable these shape preserving transformations are poorly understood. We used in situ liquid-phase transmission electron microscopy to follow the evolution from amorphous calcium carbonate to calcite in the presence of additives. A combination of contrast analysis and infrared spectroscopy shows that Mg ions, which are widely present in seawater and biological fluids, alter the transformation pathway in a concentration-dependent manner. The ions bring excess (structural) water into the amorphous bulk so that a direct transformation is triggered by dehydration in the absence of morphological changes. Molecular dynamics simulations suggest Mg-incorporated water induces structural fluctuations, allowing transformation without the need to nucleate a separate crystal. Thus, the obtained calcite retains the original morphology of the amorphous state, biomimetically achieving the morphological control of crystals seen in biominerals
crystallization, biomineralization, calcium carbon↗
Root hairs vs. trichomes: Not everyone is straight!
Trichomes show 47 morphological phenotypes, while literature reports only two root hair phenotypes in all plants. However, could hair-like structures exist below-ground in a similar wide range of morphologies like trichomes? Genetic mutants and root hair stress phenotypes point to the possibility of uncharacterized morphological variation existing belowground. For example, such root hairs in Arabidopsis (Arabidopsis thaliana) can be wavy, curled, or branched. We found hints in the literature about hair-like structures that emerge before root hairs belowground. As such, these early emerging hair structures can be potential exceptions to the contrasting morphological variation between trichomes and root hairs. Here, in this work, we show a previously unreported ‘hooked’ hair structure growing below-ground in common bean. The unique ‘hooking’ shape distinguishes the ‘hooked hair’ morphologically from root hairs. Currently, we cannot fully characterize the phenotype of our observation due to the lack of automated methods for phenotyping root hairs. This phenotyping bottleneck also handicaps the discovery of more morphology types that might exist below-ground as manual screening across species is slower than computer-assisted high-throughput screening.
59 BASIC BIOLOGICAL SCIENCES↗
Chain Redistribution Stabilizes Coexistence Phases in Block Copolymer Blends
The nanoscale morphologies of block copolymer (BCP) thin films are determined by chain architecture. Experimental studies of thin film blends of different BCP chain types have demonstrated that blending can stabilize new motifs, such as coexistence phases. Here, we deploy coarsegrained molecular dynamics (MD) simulations in order to better understand the self-assembly behavior of BCP blend thin films. Here, we consider blends of lamella- and cylinder-forming BCP chains, studying their morphological makeup, the chain distribution within the morphology, and the underlying polymer chain conformations. Our simulations show that there are local concentration deviations at the scale of the morphological objects that dictate the local structure, and that BCP chains redistribute within the morphology so as to stabilize the structure. Underlying these effects are measurable distortions in the BCP chain conformations. The conformational freedom afforded by BCP blending stabilizes defects and allows coexistence phases to appear, while also leading to kinetic trapping effects. These results highlight the power of blending in designing the morphology that forms.
36 MATERIALS SCIENCE↗
Contrasting thermally-induced structural and microstructural evolution of alumino-silicates with tubular and planar arrangements: Case study of halloysite and kaolinite
Materials with the similar chemical structures but different morphological organization exhibit considerable differences in thermally induced chemo-morphological evolution. With recent advancements in multi-scale X-ray scattering measurements, it is now possible to non-invasively probe the structural and microstructural evolution of such materials. In this study, we investigate the chemo-morphological evolution of halloysite and contrast the results with those for kaolinite. Halloysite and kaolinite have tubular and planar morphologies, respectively. Both materials are alumino-silicates comprising silica tetrahedra (T) and alumina octahedra (O) organized in a TO structure. Four distinct stages in the structural evolution were identified. Stages I, II, III, and IV correspond to temperature ranges of 25 to 125 °C, 125 to 400 °C, 400 to 625 °C, and 625 to 875 °C. Major structural changes correspond to the removal of interlayer/adsorbed water in stage I, the existence of the halloysite structure without interlayer water in stage II, dehydroxylation of halloysite in stage III, and the conversion of ordered halloysite to amorphous meta-halloysite in stage IV. Additionally, heating halloysite up to 875 °C resulted in slight widening of the nanotubes, as the average pore radius increased from 6.4 nm to 6.6 nm. Heating also resulted in an increase of wall thickness of the nanotubes from ~120 nm (25 °C) to 161 nm (875 °C). The increase in the halloysite nanotube diameter was attributed to the expansion of the structure and an increase in the surface roughness. The pore sizes in halloysite nanotubes were also confirmed using N 2 adsorption-desorption and nano-X-ray computed tomography (nano-XCT) measurements. The interlayer basal spacing in halloysite changed from 9.8 Å to 7.2 Å after the removal of interlayer water. At temperatures in the range of 625 to 875 °C, heating halloysite causes a small widening of nanotube pores and a minor increase in the surface area. In contrast, the interlayer spacing in kaolinite collapses on heating which reduces the nanoscale porosity. Furthermore, these studies demonstrate the differences in the chemo-morphological evolution of alumino-silicates with tubular and planar morphologies.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Surface diffusion manifestation in electrodeposition of metal anodes
Metal anode-based battery systems have been deemed indispensable towards energy storage renaissance engendering extensive research into strategies countering dendritic growth of metal electrodeposition. Fundamentally, the morphological evolution of a material is uniquely characterized by the heights of its self-diffusion barrier across multiple pathways. Herein, based on a coarse-grained kinetic Monte Carlo method, we derive insights into the nucleation and growth of metallic electrodeposits in liquid electrolytes, governed by surface self-diffusion characteristics cognizant of the diverse diffusion routes including terrace, away from step and interlayer pathways. We deconvolve the roles played by each of these surface diffusion mechanisms in conjunction with the electrochemical reaction rate on the deposition morphology regime (film vs. mossy vs. fractal). We identify interlayer diffusion as the predominant morphology-determining mechanism; dendrite-free deposition even at moderate current rates constrains this diffusion barrier to an upper limit. Additionally, we highlight subtle features amidst the realm of the morphological growth assortment that connect to the cell's electrochemical performance. Finally, we delineate morphological features of Li, Na, Mg and Al based on their respective surface diffusion barriers and applied overpotentials, and provide a baseline for the interpretation of experimental observations. This fundamental study sheds light on the mesoscale underpinnings of morphological variances in mono-valent and multi-valent metal electrodeposition.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Kinetic processes of phase separation and aggregation behaviors in slot-die processed high efficiency Y6-based organic solar cells
Morphological optimization has proved to be one crucial factor contributing to the 19% efficiency of Y6-based organic solar cells (OSCs). Although the relationship between component miscibility and film morphology has been established, it has not been clarified how the film formation processes proceed, especially for methods compatible with large-area fabrication, i.e. slot-die coating, which restricts the further optimization of the morphology. Herein, we comprehensively investigate the effect of miscibility and the film-formation kinetic process on film morphology during processing with different solvents. A highest power conversion efficiency (PCE) of 17.38% can be obtained in a D18:Y6 device processed with slot-die coating in an open-air environment. However, due to their relatively poor miscibility, incorporating a trace amount of chlorobenzene (CB) into CF can sufficiently promote Y6 aggregation, leading to increased phase separation and thus the average PCE drops to 15.16%. In contrast, a PM6:Y6 blend shows insensitive changes in the kinetic process as well as the final morphology, and thus in the comparable PCEs when cast with different solvents, which is ascribed to their relatively good miscibility. As a result, this work provides scientific guidelines for device optimization by combining the intermediate gap from miscibility to kinetic process and their impact on final morphology.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Disturbed, diffuse, or just missing? A global study of the H I content of Hickson compact groups
Hickson compact groups (HCGs) are dense configurations of four to ten galaxies, whose H I morphology appears to follow an evolutionary sequence of three phases, with gas initially confined to galaxies, then significant amounts spread throughout the intra-group medium, and finally with almost no gas remaining in the galaxies themselves. It has also been suggested that several groups may harbour a diffuse H I component that is resolved out by interferometric observations. The H I deficiency of HCGs is expected to increase as the H I morphological phase progresses along the evolutionary sequence. If this is the case, H I deficiency would be a rough proxy for the age and evolutionary state of a HCG. We aim to test this hypothesis for the first time using a large sample of HCGs and to investigate the evidence for diffuse H I in HCGs. We performed a uniform reduction of all publicly available VLA H I observations (38 HCGs) with a purpose-built pipeline that also maximises the reproducibility of this study. The resulting H I data cubes were then analysed with the latest software tools to perform a manual separation of emission features into those belonging to galaxies and those extending into the intra-group medium. We thereby classified the H I morphological phase of each group as well as quantified their H I deficiency compared to galaxies in isolation. We find little evidence that H I deficiency can be used as a proxy for the evolutionary phase of a compact group in either of the first two phases, with the distribution of H I deficiency being consistent in both. However, for the final phase, the distribution clearly shifts to high H I deficiencies, with more than 90% of the expected H I content typically missing. Across all HCGs studied, we identify a few cases where there is strong evidence for a diffuse gas component in the intra-group medium, which might be detectable with improved observations. We also classify a new sub-phase where groups contain a lone H I -bearing galaxy, but are otherwise devoid of gas. The new morphological phase we have identified is likely the result of an evolved, gas-poor group acquiring a new, gas-rich member. The large spread of H I deficiencies in the first two morphological phases suggests that there is a broad range of initial H I content in HCGs, which is perhaps influenced by large-scale environment, and that the timescale for morphological changes is, in general, considerably shorter than the timescale for the destruction or consumption of neutral gas in these systems.
79 ASTRONOMY AND ASTROPHYSICS↗
The co-evolution of strong AGN and central galaxies in different environments
We exploit a sample of 80 000 Sloan Digital Sky Survey central galaxies to investigate the effect of active galactic nucleus (AGN) feedback on their evolution. We trace the demographics of optically selected AGN (Seyferts) as a function of their internal properties and environment. We find that the preeminence of AGN as the dominant ionizing mechanism increases with stellar mass, overtaking star formation for galaxies with M stellar ≥ 10 10 M ⊙ . The AGN fraction changes systematically with the galaxies’ star formation activity. Within the blue cloud, this fraction increases as star formation activity declines, reaching a maximum near the green valley (~17 ± 4 per cent), followed by a decrease as the galaxies transition into the red sequence. This systematic trend provides evidence that AGN feedback plays a key role in regulating and suppressing star formation. In general, Seyfert central galaxies achieve an early-type morphology while they still host residual star formation. This suggests that, in all environments, the morphology of Seyfert galaxies evolves from late- to early-type before their star formation is fully quenched. Stellar mass plays an important role in this morphological transformation: while low-mass systems tend to emerge from the green valley with an elliptical morphology (T-Type ∼ −2.5 ± 0.7), their high-mass counterparts maintain a spiral morphology deeper into the red sequence. In high-stellar mass centrals, the fraction of Seyferts increases from early- to late-type galaxies, indicating that AGN feedback may be linked with the morphology and its transformation. As a result, our analysis further suggests that AGN are fuelled by their own host halo gas reservoir, but when in group centrals can also increase their gas reservoir via interactions with satellite galaxies.
79 ASTRONOMY AND ASTROPHYSICS↗
The Dynamic of Complex Two-Phase Mixtures During Coarsening: From Dendritic to Bicontinuous Mixtures
Dendrites are tree-like crystals that frequently form during the solidification of castings. In systems with nearly isotropic interfacial energy, these dendrites possess secondary and sometimes even tertiary arms, and lead to morphologically complex two-phase mixtures. Dealloying, in which one component is selectively leached, leads to nanoporous structures that have proven useful for many technological applications. These bicontinuous two-phase mixtures are topologically and morphologically complex with spatially varying mean and Gaussian curvatures. The evolution of these structures during coarsening is of considerable technological importance since the morphology of the dendrites and nanoporous structure sets the properties of the resulting material. During coarsening, the total surface area per volume of the mixture decreases, thus resulting in an increase in the size-scale of the two-phase mixture. The evolution of interfacial morphology of these interconnected two-phase mixtures is being studied using large-scale computer simulations. The simulations are used to develop a theory of coarsening in these systems that will elucidate the impact of the complicated morphology found in dendritic and nanoporous systems on the coarsening process. The experiments employ four-dimensional X-ray microtomography, which enables the morphology of the two-phase mixture to be followed in three dimensions and time (an additional dimension). The experiments also serve as a test of simulations and theory of the coarsening process, as well as to provide initial conditions for the simulations. Through these experiments and theory, we aim to develop a comprehensive description of coarsening in these complex and technologically important two-phase mixtures.
36 MATERIALS SCIENCE↗
Mechanical Properties of Polyisoprene-Based Elastomer Composites
Herein we have explored the origins of mechanical reinforcement in elastomers filled with polymer-grafted nanoparticles (NPs). The brush chains are constructed from the same monomers as the polymer melt, although they have different microstructures (i.e., different amounts of trans and cis isomers). The NPs display a variety of morphologies depending on variations in the graft density of the polymers, with these morphologies hardly changing when the matrix (and the grafts) is cross-linked using dicumyl peroxide (DCP). NMR measurements show that the cross-link densities depend only on the DCP content and are independent of NP morphologies. We find that the elastic moduli of these materials are strongly dependent on the NP morphology but that the maximum reinforcement occurs when the NPs percolate, in a manner where the cores are exposed enough to have strong enthalpic interactions; these interactions could either be due to direct core–core van der Waals attractions or due to bridging interactions driven by polymers adsorbed on adjacent NPs. The nonlinear mechanical response of these materials is less sensitive to changes in NP morphology and loading. These results emphasize the important role of the exposed NP surface in determining the moduli of cross-linked elastomers. This last aspect is apparently less relevant for the corresponding uncross-linked melts filled with NPs.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Synergistic Enzyme Mixtures to Realize Near-Complete Depolymerization in Biodegradable Polymer/Additive Blends
Embedding catalysts inside of plastics affords accelerated chemical modification with programmable latency and pathways. Nanoscopically embedded enzymes can lead to near-complete degradation of polyesters via chain-end mediated processive depolymerization. The overall degradation rate and pathways have a strong dependence on the morphology of semicrystalline polyesters. Yet, most studies to date focus on pristine polymers instead of mixtures that contain additives and other components despite their nearly universal use in plastic production. Here, for this study, additives are introduced to purposely change the morphology of polycaprolactone (PCL) by increasing the bending and twisting of crystalline lamellae. These morphological changes immobilize chain ends preferentially at the crystalline/amorphous interfaces and limit chain-end accessibility by the embedded processive enzyme. This chain-end redistribution reduces the polymer-to-monomer conversion from >95% to less than 50%, causing formation of highly crystalline plastic pieces, including microplastics. By synergizing both random chain scission and processive depolymerization, it is feasible to navigate morphological changes in polymer/additive blends and to achieve near-complete depolymerization. The random scission enzymes in the amorphous domains create new chain ends that are subsequently bound and depolymerized by processive enzymes. Present studies further highlight the importance to consider how the host polymer's morphologies affect the reactions catalyzed by embedded catalytic species.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Qualitative assessment of uranium ore concentrates and related materials using scanning electron microscopy
Several studies have evaluated the morphology of uranium compounds produced under controlled conditions at the laboratory scale, but it is unclear whether the morphological characteristics of these materials persist in commercially produced uranium ore concentrates (UOCs). To assess the morphology in “real-world” UOCs, we qualitatively evaluated the morphological profile of secondary electron images from over 100 commercial UOCs using a previously published lexicon. We observe differences between samples with differing chemical composition and samples with similar chemical composition and differing provenance. Further, this work contextualizes morphology for commercially produced UOCs and will provide a basis for future machine learning efforts.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Investigation of process history and underlying phenomena associated with the synthesis of plutonium oxides using Vector Quantizing Variational Autoencoder
Accurate, high throughput, and unbiased analysis of plutonium oxide particles is needed for analysis of the phenomenology associated with process parameters in their synthesis. Compared to qualitative and taxonomic descriptors, quantitative descriptors of particle morphology through scanning electron microscopy (SEM) have shown success in analyzing process parameters of uranium oxides. Among other candidates, a neural network called a Vector Quantizing Variational Autoencoder (VQ-VAE) has shown the ability to quantitatively describe particle morphology to attain >85% accuracy in identifying uranium oxide processing routes. We utilize a VQ-VAE to quantitatively describe plutonium dioxide (PuO 2 ) particles created in a designed experiment and investigate their phenomenology and prediction of their process parameters. PuO 2 was calcined from Pu(III) oxalates that were precipitated under varying synthetic conditions that related to concentrations, temperature, addition and digestion times, precipitant feed, and strike order; the surface morphology of the resulting PuO 2 powders were analyzed by SEM. A pipeline was developed to extract and quantify useful image representations for individual particles with the VQ-VAE, then further reduce the dimensionality of the feature space using a bottlenecking neural network fit to perform multiple classification tasks simultaneously. The reduced feature space could predict process parameters with greater than 80% accuracies for some parameters with a single particle. They also showed utility for grouping particles with similar surface morphology characteristics together. Both the clustering and classification results reveal valuable information regarding which chemical process parameters chiefly influence the PuO 2 particle morphologies: strike order and oxalic acid feedstock. Doing the same analysis with multiple particles was shown to improve the classification accuracy on each process parameter over the use of a single particle, with statistically significant results generally seen with as few as four particles in a sample.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NanoPSD: A software for automatic detection of Nano-Particle Shape Distribution in electron microscopy images
Accurate quantification of the size and morphology of nanoparticles from electron microscopy (EM) images is essential to understand growth mechanisms, surface reactivity, and functional behavior in nanoscale materials. Manual analysis remains slow, subjective, and difficult to reproduce in large datasets. We introduce NanoPSD (Nano-Particle Shape Distribution), an open-source and fully automated framework for quantitative particle detection and morphology analysis from EM images. NanoPSD integrates adaptive contrast enhancement, polarity-agnostic scale-bar detection, Optical Character Recognition (OCR)-based calibration, and classical segmentation via Otsu thresholding with morphological refinement. Particle contours are used to extract geometric descriptors, including equivalent circular diameter, aspect ratio, circularity, and solidity, enabling automated classification into spherical, rod-like, and aggregate morphologies. The framework supports both single-image and batch processing, generating publication-quality visualizations, LaTeX-ready tables, and structured comma-separated values (CSV) datasets. As a demonstration, we applied NanoPSD to plasma-synthesized nanoparticle samples diagnosed via transmission electron microscopy (TEM). The code produced statistically robust size and morphology distributions spanning a few to tens of nanometers with minimal user supervision. The pipeline demonstrates high reproducibility and scalability, processing large image collections with consistent calibration and output formatting. Its modular design enables seamless integration of future deep-learning-based segmentation models, providing a pathway toward intelligent, data-driven electron microscopy analysis.
36 MATERIALS SCIENCE↗
On the measurement of shape: With applications to lunar regolith
With the renewed commitment from NASA and other commercial entities for a presence on the Moon, the importance of understanding the characteristics of lunar regolith and how to utilize it have become the target of increasing scrutiny. Much of what is known about lunar regolith was collected during and immediately after the Apollo program, however, analytical techniques and instrumentation have advanced in leaps and bounds in the subsequent decades. Specifically, dynamic image analysis systems have advanced to the point that millions of particles can have morphological characteristics automatically determined in relatively short time frames. Particle morphological data was collected on several lunar samples and a pair of widely used regolith simulants to ascertain the accuracy of these simulants and to explore statistical analysis methods of these large datasets. It is found that these morphology datasets can vary widely depending on the particle size of the particles, and simple averaging of the data skews the results heavily towards the numerically abundant size ranges, the fines. Different reporting methods are suggested to ameliorate these problems. When applied to the lunar regolith, the particles are noted to be less morphologically complex than initially suspected. Compared to the lunar material, the simulants are found to contain some more morphological variability and angular grains. Such difference is likely due to the wildly different comminution processes that these different powder systems are subjected to.
2D shape↗