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Resonant Soft X-ray Scattering Reveals Hierarchical Structure in a Multicomponent Vapor-Deposited Glass
Multiphase vapor-deposited glasses are an important class of materials for organic electronics, particularly organic photovoltaics and thermoelectrics. These blends are frequently regarded as molecular alloys and there have been few studies of their structure at nanometer scales. Here, in this work, we show that a codeposited system of TPD (N,N'-bis(3-methylphenyl)-N,N'-diphenylbenzidine) and DO37 (disperse orange 37), two small molecule glass-formers, separates into amorphous, compositionally distinct phases with a domain size and spacing ca. 10s of nanometers that depends on substrate temperature during deposition. Domains rich in one of the two components become larger and more pure at higher deposition temperatures. We use resonant soft X-ray scattering (RSoXS) complemented with atomic force microscopy (AFM) and photoinduced force microscopy to measure the phase separation, topography, and purity of the deposited films. A forward-simulation approach to RSoXS analysis, the National Institute of Standards and Technology RSoXS Simulation Suite (NIST RSoXS simulation suite), is used with models developed from AFM images to evaluate the energy dependence of scattering across multiple length scales and interpret the RSoXS with respect to structure within the films. We find that the RSoXS is sensitive to a length scale of phase separation buried within the film that is consistent with the surface composition profile, and correlates to the topography to an extent that depends on substrate temperature. We demonstrate that vacuum scattering, which is often ignored in RSoXS analysis, contributes significantly to the features and energy dependence of the RSoXS pattern, and then illustrate how to properly account for vacuum scattering to analyze films with significant roughness. We then use this analysis framework to understand structure development mechanisms that occur during vapor deposition of a TPD-DO37 codeposited glass with results that outline paths to tune morphology in multicomponent materials.
Hierarchal structures tuned electrocaloric and electromechanical performance in PVDF-based tetrapolymers
Ferroelectrics with multifunctionalities are gaining increased interest in self-actuated electrocaloric effect (ECE) refrigerators. However, achieving high ECE and electromechanical (EM) coupling concomitantly for maximum heat transfer remains challenging. Here we present the structure-property relationship for poly(vinylidene fluoride-co-trifluoroethylene-co-chlorofluoroethylene-co-double bond), P(VDF-TrFE-CFE-DB), tetrapolymer, which exhibited a high ECE entropy change of 66.5 J Kg −1 K −1 and EM strain of −6.1%. We show that thermal treatment can be a key factor influencing multifunctional properties. High-temperature annealing incorporates DB and CFE units into crystalline grains to form extended-chain crystals, enabling CFE units to induce relaxor behavior and DB units to induce large structural changes at low electric fields. This synergy leads to an enhancement in both ECE and EM performances. Furthermore, at an optimized temperature of 50 °C, the annealed films exhibit giant cross-energy coupling, achieving ECE and EM performances of 100.8 J Kg −1 K −1 and −7.6%. This study provides insights into developing new ferroelectric polymers with electroactive multifunctionalities.
Hierarchical structural performance modeling for qualification of metal AM components.
Abstract not provided.
Interfacial Self-Assembly of Hierarchically Structured Nanoparticles with Photocatalytic Activity.
Abstract not provided.
Hierarchical structural performance models for qualification of metal AM components.
Abstract not provided.
Hierarchically structured MoO2/dopamine-derived carbon spheres as intercalation electrodes for lithium-ion batteries
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Controlled synthesis of hierarchically-structured hybrid materials through peptoid engineering
This disclosure concerns a method for making a hybrid organic/inorganic material having an architecture. The method includes combining a peptoid comprising a sequence of N-substituted glycine residues and an inorganic material or inorganic material precursor to form a hybrid organic/inorganic material comprising the peptoid and the inorganic material, the hybrid organic/inorganic material having an architecture based at least in part on the peptoid sequence. The hybrid organic/inorganic materials include a cluster of nanoparticles of an inorganic material and peptoids, the cluster formed by random attachment of nanoparticles to one another by peptoid-peptoid and peptoid-nanoparticle surface interactions, wherein the hybrid material has an architecture based at least in part on the peptoid sequence.
Optimizing group structures using hierarchical division
Creating group structures with few groups that give low errors is a difficult problem in reactor analysis. In recent years, automated optimization techniques have been applied to this task. We continue this trend by applying the hierarchical division algorithm to generate optimized group structures that minimize a cost function. At each stage, the algorithm adds a single group boundary to an existing group structure, dividing one group into two to increase the resolution of the group structure. The location of the added boundary is the one that gives the lowest error over all possible new boundary locations. Our implementation requires a beginning group structure, a set of candidate new boundary locations, and a set of reference reaction rates. As a proof of concept, we used WIMS-69 as the initial group structure, XMAS-172 as the ending group structures, and a 344-group reference group structure. Testing on two simple, homogenized reactor problems, we found that hierarchical division was able to reduce the error by a factor of around 5 with an increase of only 15% in the number of groups. Because hierarchical division can get stuck in local minima, it often reaches a plateau in its error reduction capability as many groups are added. Nevertheless, we find hierarchical division has strong potential to make good group structures into great group structures at a modest increase in computational cost. (authors)
Deformation-enhanced hierarchical multiscale structure heterogeneity in a Pd-Si bulk metallic glass
Here, the multiscale structures in a Pd 82 Si 18 binary bulk metallic glass before and after deformation were studied using electron microscopies, high-energy synchrotron X-ray diffraction, and small-angle scattering techniques. The experimental results revealed an enhancement of hierarchical structure heterogeneities on multiple length scales after deformation. Hierarchical multiple shear bands of high number density were observed after bending, introducing complex but periodically distributed residual strain. Pair distribution function analysis revealed that the connectivity of the short-range clusters on the medium-range scale determines the packing density difference between the tension side and the compression side in the sample after bending. In-situ synchrotron X-ray diffraction study also revealed a transformation of connection modes among short-range clusters under uniaxial tension and compression, which is consistent with those of triaxial tension/compression parts upon bending in Pd 82 Si 18 glassy alloys. The nanoscale heterogeneities for metallic glasses after deformation observed by small-angle scattering and transmission electron microscopy may be attributed to the nanoscale amorphous phase separation and interacting multiple shear bands enhanced by plastic deformation. Our findings suggested that the enhancement of hierarchical heterogeneous structure on multiple length scales may explain the excellent plasticity of Pd-Si glassy alloys, deepening the understanding of structure-property relation during plastic deformation in metallic glasses.
Emerging hierarchical dislocation structures: Insights from scanning electron microscopy-electron backscatter diffraction in situ tensile testing and multifractal analysis
Understanding the evolution of dislocation structures during plastic deformation is critical for predicting the mechanical performance of metallic materials. In this work, we applied in situ scanning electron microscopy/electron backscatter diffraction tensile testing combined with multifractal (MF) analysis to assess deformation-induced dislocation structure evolution in solution-annealed 304 L stainless steel, both in its as-received and neutron-irradiated states (5.4 displacements per atom). The analysis of kernel average misorientation patterns revealed the formation of hierarchical dislocation arrangements that exhibit clear MF scaling behavior. Despite pronounced visual differences between nonirradiated and irradiated specimens—most notably, the appearance of dislocation channels after irradiation—the singularity spectra suggest that both conditions give rise to similar underlying hierarchical structures. MF analysis provides a quantitative measure of the spatial complexity and self-organization of dislocation patterns, highlighting the accelerated emergence and evolution of the dislocation structures in irradiated polycrystalline materials, as well as the limitation of their spatial extent. The findings indicate that irradiation not only modifies microstructure but also alters correlation-driven dislocation organization. More generally, they demonstrate that MF analysis is a powerful tool for probing mesoscale deformation mechanisms.
Hierarchical domain structures associated with oxygen octahedra tilting patterns in lead-free (Bi 1/2 Na 1/2 )TiO 3
Hierarchical domain structures associated with oxygen octahedra tilting patterns were observed in lead-free (Bi 1/2 Na 1/2 )TiO 3 ceramics using aberration-corrected high-resolution transmission electron microscopy (HRTEM). Three types of domains are induced by distinct mechanisms: the 'orientation-domain' is induced at micrometer scale formed by different tilting orientations of the oxygen octahedra, the 'meso-chemical-domain' occurs at a few tens of nanometer scale by chemical composition variation on the A-site in the ABO 3 perovskite structure, and the 'nano-cluster-region' runs across several unit-cells with apparent A-site cation segregation with oxygen vacancies clustering around Na cations. Based on HRTEM amplitude contrast imaging (ACI), the correlation between the oxygen octahedral tilting pattern and compositional non-stoichiometry was established. The role of the hierarchical domain structure associated with the tilting patterns of the oxygen octahedra on the ferroelectric behavior of (Bi 1/2 Na 1/2 )TiO 3 is also discussed.
Hierarchical Epoxy Structures via Tunable Polymerization-Induced Phase Separation Combined with Additive Manufacturing
Polymerization-induced phase separation (PIPS) allows for the control of thermoset morphologies and properties, enabling the tuning of domain sizes and thermomechanical response. However, its use in generating substructural features in additively manufactured materials has been limited. In this work, we combine epoxy PIPS with UV curable acrylate and rheological modifiers to print nano- to macro-phase separating materials via a two-step, dual-cure approach. This method enables direct ink write printing of hierarchical structures with both controlled morphologies through phase separation and macroscale architecture through print design. We find that formulations for phase-separating materials require judicious incorporation of additives to enable printability and to provide sufficient green strength. Atomic force microscopy-nano infrared mapping reveals tunable, reticulated nano- to micron-scale domains of the resultant multiphase materials and their morphology changes due to additives, resulting in alterations to thermomechanical and tensile properties. Shape memory behavior is also demonstrated through multimaterial additive manufacturing of epoxies with functionally graded internal morphology using active mixing techniques, highlighting this method’s ability to fabricate complex architectures with controlled morphologies and thermomechanical response.
Ballistic ion transport through hierarchically-ordered-structure polymer binder
Achieving ballistic ion transport in a mixed electronic-ionic conductive polymer, its hierarchically ordered structure (HOS) facilitates ion diffusion and results in solid-state Li + conductivity in the range of 10 −4 to 10 −3 S cm −1 from −20 to 70 °C.
Mechanical responses of architected boron carbide-aluminum lattice composites fabricated via reactive metallic infiltration of hierarchical pore structures
The incorporation of micro and nanoscale constituents in a hierarchical order improves mechanical properties of bulk structures while inducing controlled deformation. However, these features have seldomly been applied to the fabrication of cermet materials due to manufacturing constraints. Here, overcoming previous limitations, boron carbide cermets with embedded aluminum lattices were produced using a combination of additive manufacturing and gelcasting techniques. Kelvin cell and octet truss scaffolds were printed, cast and burned out so the negative volume could be infiltrated with metal to form an architected cermet. Computed microtomography scans reveal full aluminum infiltration of the volume with high fidelity to the target architecture. Equibiaxial flexural tests showed localized crack propagation in lattice-reinforced cermets and that samples with imbedded architecture required nearly double the energy for complete failure. Overall, the addition of an internal aluminum lattice limits abrupt fracture of the composite and provides a method for tuning its mechanical response with architected ratios of metal to ceramic.
Wood Carbon Based Single-Atom Catalyst for Rechargeable Zn–Air Batteries
Low-cost and efficient oxygen reduction reaction (ORR)/oxygen evolution reaction (OER) bifunctional electrocatalysts are vital for the applications of rechargeable Zn-air batteries (ZABs). Given the high catalytic activity of single-atom catalysts (SACs), preparing SACs on a large scale for ZABs is desirable but remains challenging. Herein, in situ formation of single-atom Fe-N-C catalysts on plate wood-based porous carbon is achieved via a facile Lewis acid pretreatment and carbonization process. Lewis acid FeCl3 pretreatment on the cell wall of wood not only produces abundant microchannels but also successfully introduces atomically dispersed Fe-N active species into the hierarchical structure. Such uniformly dispersive SACs on the hierarchical structure enhance the ORR/OER performance and durability. A ZAB using the catalyst in the cathode shows a high power density (70.2 mW cm -2 , at quasi solid state) and long-term stability. This work provides a new path for the large-scale preparation of high-performance SACs.
Genarris 2.0: A Random Structure Generator for Molecular Crystals
Genarris is an open source Python package for generating random molecular crystal structures with physical constraints for seeding crystal structure prediction algorithms and training machine learning models. Here we present a new version of the code, containing several major improvements. A MPI-based parallelization scheme has been implemented, which facilitates the seamless sequential execution of user-defined workflows. A new method for estimating the unit cell volume based on the single molecule structure has been developed using a machine-learned model trained on experimental structures. A new algorithm has been implemented for generating crystal structures with molecules occupying special Wyckoff positions. A new hierarchical structure check procedure has been developed to detect unphysical close contacts efficiently and accurately. New intermolecular distance settings have been implemented for strong hydrogen bonds. To demonstrate these new features, we study two specific cases: benzene and glycine. Genarris finds the experimental structures of the two polymorphs of benzene and the three polymorphs of glycine. Program summary Program Title: Genarris 2.0 Program Files doi: http://dx.doi.org/10.17632/grx6mz4pjn.1 Licensing provisions: BSD-3 Clause Programming language: Python, C External routines/libraries: Spglib, ASE, pymatgen, SciPy, mpi4py, scikit-learn, PyTorch, FHI-aims. Nature of problem: Molecular crystal structure prediction. Solution method: Genarris 2.0 generates molecular crystal structures over the 230 space groups, on general and special Wyckoff positions, using physical constraints. Down-sampling of the generated structures may be performed subsequently, based on molecular crystal packing descriptors and an unsupervised machine learning algorithm. Lastly, ab initio structure relaxation may be performed for the final pool. Depending on the user-defined workflow implemented, Genarris may be used to generate diverse molecular crystal datasets to seed evolutionary algorithms or to train machine learning algorithms or as a standalone crystal structure prediction method. Restrictions: For crystal structure generation, the molecule of interest must be semi-rigid with no bond rotational degrees of freedom. Unusual features: Genarris 2.0 is a highly distributed program, making use of MPI for Python parallelization. The user has the ability to design and implement workflows by executing a user-defined list of procedures. Genarris 2.0 offers new features including a machine learning model for estimating the molecular volume in the solid state from the single molecule structure, structure generation in special Wyckoff positions of space groups, hierarchical structure checks including rigorous treatment of non-orthogonal structures, and clustering and down-selection workflows combining first principles simulations with machine learning. (C) 2020 Elsevier B.V. All rights reserved.