Bulk supercrystalline ceramic-organic nanocomposites: New processing routines and insights on the mechanical behavior

In the strive to produce nature-inspired hierarchical materials with an enhanced combination of mechanical properties, supercrystalline ceramic-organic nanocomposites have been produced in bulk form and characterized from a variety of perspectives. Through an interdisciplinary collaboration at the crossroad between materials science, chemistry and mechanical engineering, a bottom-up approach has been designed. It consists of a sequence of self-assembly, pressing and heat treatment, and it leads to macroscopic poly-supercrystalline materials with exceptional mechanical properties and behavior. The crosslinking of the organic phase induced by the heat treatment does not only increase the materials’ stiffness, hardness and strength (elastic modulus up to 70 GPa, hardness up to 5 GPa and bending strength up to 630 MPa), but alters also their constitutive response. Fracture toughness values higher than theoretical predictions have emerged (~ 1 MPa·m1/2), implying the presence of extrinsic toughening mechanisms, such as the crack-path deviation observed at indents’ corners. Ex-situ nanoindentation and in-situ SAXS/microcompression studies also suggest the possibility for supercrystalline materials to accommodate compressibility and plastic-like deformation. Defects analogous to the ones typically observed in crystalline lattices, such as stacking faults, dislocations and slip bands, are detected at the superlattice scale (even if one order of magnitude larger than the atomic one, and with interactions among the nano-building blocks controlled by the organic phase). Correlations between defects, processing and mechanical properties have been drawn by adapting the classic theories of mechanical behavior of materials. These same materials are additionally being used as bricks for the development of novel hierarchical composites, via additive manufacturing or fluidized bed techniques. Please click Additional Files below to see the full abstract

Iron oxide-based nanostructured ceramics with tailored magnetic and mechanical properties: Development of mechanically robust, bulk superparamagnetic materials

Nanostructured iron-oxide based materials with tailored mechanical and magnetic behavior are produced in bulk form. By applying ultra-fast heating routines via spark plasma sintering (SPS) to supercrystalline pellets, materials with an enhanced combination of elastic modulus, hardness and saturation magnetization are achieved. Supercrystallinity-namely the arrangement of the constituent nanoparticles into periodic structures-is achieved through self-assembly of the organically-functionalized iron oxide nanoparticles. The optimization of the following SPS regime allows the control of organics' removal, necking, iron oxide phase transformations and nano-grain size retention, and thus the fine-tuning of both mechanical properties and magnetic response, up until the production of bulk mm-size superparamagnetic materials.Deusche Forschungsgemeinschaft (DFG

Hierarchical supercrystalline nanocomposites through the self-assembly of organically-modified ceramic nanoparticles

Biomaterials often display outstanding combinations of mechanical properties thanks to their hierarchical structuring, which occurs through a dynamically and biologically controlled growth and self-assembly of their main constituents, typically mineral and protein. However, it is still challenging to obtain this ordered multiscale structural organization in synthetic 3D-nanocomposite materials. Herein, we report a new bottom-up approach for the synthesis of macroscale hierarchical nanocomposite materials in a single step. By controlling the content of organic phase during the self-assembly of monodisperse organically-modified nanoparticles (iron oxide with oleyl phosphate), either purely supercrystalline or hierarchically structured supercrystalline nanocomposite materials are obtained. Beyond a critical concentration of organic phase, a hierarchical material is consistently formed. In such a hierarchical material, individual organically-modified ceramic nanoparticles (Level 0) self-assemble into supercrystals in face-centered cubic superlattices (Level 1), which in turn form granules of up to hundreds of micrometers (Level 2). These micrometric granules are the constituents of the final mm-sized material. This approach demonstrates that the local concentration of organic phase and nano-building blocks during self-assembly controls the final material's microstructure, and thus enables the fine-tuning of inorganic-organic nanocomposites' mechanical behavior, paving the way towards the design of novel high-performance structural materials.The authors gratefully acknowledge the financial support from the German Research Foundation (DFG) via the SFB 986-M3, projects A1, A6, Z2, and Z3. We thank Dr. F. Beckmann (Helmholtz-Zentrum Geesthacht, Geesthacht, Germany) for scanning the sample with the technique SRµCT and for reconstructing the slices, and Dr. I. Greving (Helmholtz-Zentrum Geesthacht, Geesthacht, Germany) for her inputs on SRµCT. Dr. F. Brun (National Institute of Nuclear Physics, Trieste, Italy) is acknowledged for the discussion regarding quantitative analysis using Pore3d

Determination of the packing fraction in photonic glass using synchrotron radiation nanotomography

Photonic glass is a material class that can be used as photonic broadband reflectors, for example in the infrared regime as thermal barrier coating films. Photonic properties such as the reflectivity depend on the ordering and material packing fraction over the complete film thickness of up to 100 μm. Nanotomography allows acquiring these key parameters throughout the sample volume at the required resolution in a non-destructive way. By performing a nanotomography measurement at the PETRA III beamline P05 on a photonic glass film, the packing fraction throughout the complete sample thickness was analyzed. The results showed a packing fraction significantly smaller than the expected random close packing giving important information for improving the fabrication and processing methods of photonic glass material in the future

Dataset of ptychographic X-ray computed tomography of inverse opal photonic crystals produced by atomic layer deposition

This data article describes the detailed parameters for synthesizing mullite inverse opal photonic crystals via Atomic Layer Deposition (ALD), as well as the detailed image analysis routine used to interpret the data obtained by the measurement of such photonic crystals, before and after the heat treatment, via Ptychographic X-ray Computed Tomography (PXCT). The data presented in this article are related to the research article by Furlan and co-authors entitled "Photonic materials for high-temperature applications: Synthesis and characterization by X-ray ptychographic tomography" (Furlan et al., 2018). The data include detailed information about the ALD super-cycle process to generate the ternary oxides inside a photonic crystal template, the raw data from supporting characterization techniques, as well as the full dataset obtained from PXCT. All the data herein described is publicly available in a Mendeley Data archive "Dataset of synthesis and characterization by PXCT of ALD-based mullite inverse opal photonic crystals" located at https://data.mendeley.com/datasets/zn49dsk7x6/1 for any academic, educational, or research purposes

Strong macroscale supercrystalline structures by 3D printing combined with self-assembly of ceramic functionalized nanoparticles

To translate the exceptional properties of colloidal nanoparticles (NPs) to macroscale geometries, assembly techniques must bridge a 106-fold range of length. Moreover, for successfully attaining a final mechanically robust nanocomposite macroscale material, some of the intrinsic NPs’ properties have to be maintained while minimizing the density of strength-limiting defects. However, the assembly of nanoscale building blocks into macroscopic dimensions, and their effective macroscale properties, are inherently affected by the precision of the conditions required for assembly and emergent flaws including point defects, dislocations, grain boundaries, and cracks. Herein, a direct-write self-assembly technique is used to construct free-standing, millimeter-scale columns comprising spherical iron oxide NPs (15 nm diameter) surface functionalized with oleic acid (OA), which self-assemble into face-centered cubic (FCC) supercrystals in minutes during the direct-writing process. The subsequent crosslinking of OA molecules results in nanocomposites with a maximum strength of 110 MPa and elastic modulus up to 58 GPa. These mechanical properties are interpreted according to the flaw size distribution and are as high as newly engineered platelet-based nanocomposites. The findings indicate a broad potential to create mechanically robust, multifunctional 3D structures by combining additive manufacturing with colloidal assembly.Financial support from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Projektnummer 192346071, SFB 986 -, the National Science Foundation CAREER Award (CMMI-1346638, to A.J.H.), and from the MIT-Skoltech Next Generation Program. A.T.L.T. was supported by a postgraduate fellowship from DSO National Laboratories, Singapore. XRM at the University of Bremen was funded within the CO 1043 12-1 (Call for Major Equipment, XRM)

An environment for relation mining over richly annotated corpora: the case of GENIA

BACKGROUND: The biomedical domain is witnessing a rapid growth of the amount of published scientific results, which makes it increasingly difficult to filter the core information. There is a real need for support tools that 'digest' the published results and extract the most important information. RESULTS: We describe and evaluate an environment supporting the extraction of domain-specific relations, such as protein-protein interactions, from a richly-annotated corpus. We use full, deep-linguistic parsing and manually created, versatile patterns, expressing a large set of syntactic alternations, plus semantic ontology information. CONCLUSION: The experiments show that our approach described is capable of delivering high-precision results, while maintaining sufficient levels of recall. The high level of abstraction of the rules used by the system, which are considerably more powerful and versatile than finite-state approaches, allows speedy interactive development and validation

The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text

BACKGROUND: Determining usefulness of biomedical text mining systems requires realistic task definition and data selection criteria without artificial constraints, measuring performance aspects that go beyond traditional metrics. The BioCreative III Protein-Protein Interaction (PPI) tasks were motivated by such considerations, trying to address aspects including how the end user would oversee the generated output, for instance by providing ranked results, textual evidence for human interpretation or measuring time savings by using automated systems. Detecting articles describing complex biological events like PPIs was addressed in the Article Classification Task (ACT), where participants were asked to implement tools for detecting PPI-describing abstracts. Therefore the BCIII-ACT corpus was provided, which includes a training, development and test set of over 12,000 PPI relevant and non-relevant PubMed abstracts labeled manually by domain experts and recording also the human classification times. The Interaction Method Task (IMT) went beyond abstracts and required mining for associations between more than 3,500 full text articles and interaction detection method ontology concepts that had been applied to detect the PPIs reported in them.RESULTS:A total of 11 teams participated in at least one of the two PPI tasks (10 in ACT and 8 in the IMT) and a total of 62 persons were involved either as participants or in preparing data sets/evaluating these tasks. Per task, each team was allowed to submit five runs offline and another five online via the BioCreative Meta-Server. From the 52 runs submitted for the ACT, the highest Matthew's Correlation Coefficient (MCC) score measured was 0.55 at an accuracy of 89 and the best AUC iP/R was 68. Most ACT teams explored machine learning methods, some of them also used lexical resources like MeSH terms, PSI-MI concepts or particular lists of verbs and nouns, some integrated NER approaches. For the IMT, a total of 42 runs were evaluated by comparing systems against manually generated annotations done by curators from the BioGRID and MINT databases. The highest AUC iP/R achieved by any run was 53, the best MCC score 0.55. In case of competitive systems with an acceptable recall (above 35) the macro-averaged precision ranged between 50 and 80, with a maximum F-Score of 55. CONCLUSIONS: The results of the ACT task of BioCreative III indicate that classification of large unbalanced article collections reflecting the real class imbalance is still challenging. Nevertheless, text-mining tools that report ranked lists of relevant articles for manual selection can potentially reduce the time needed to identify half of the relevant articles to less than 1/4 of the time when compared to unranked results. Detecting associations between full text articles and interaction detection method PSI-MI terms (IMT) is more difficult than might be anticipated. This is due to the variability of method term mentions, errors resulting from pre-processing of articles provided as PDF files, and the heterogeneity and different granularity of method term concepts encountered in the ontology. However, combining the sophisticated techniques developed by the participants with supporting evidence strings derived from the articles for human interpretation could result in practical modules for biological annotation workflows