Abstract: This study is focused on thermoresponsive glycogen-graft-poly(2-alkyl-2-oxazolines), a new group of nanostructured hybrid dendrimeric stimuli-responsive polymers connecting the body's own biodegradable polysaccharidic dendrimer glycogen with the widely tuneable thermoresponsive behavior of polypeptide-analogic poly(2-alkyl-2-oxazolines), which are known to be biocompatible. Glycogen-graft-poly(2-alkyl-2-oxazolines) were prepared by a simple one-pot two-step procedure involving cationic ring-opening polymerization of 2-alkyl-2-oxazolines followed by termination of the living cationic ends with sodium glycogenate. As confirmed by light and X-ray scattering, as well as cryo-transmission electron microscopy, the grafted dendrimer structure allows easy adjustment of the cloud point temperature, the concentration dependence and nanostructure of the self-assembled phase separated polymer by crosstalk during graft composition, the graft length and the grafting density, in a very wide range.

Abstract: The counterions are of crucial importance in determining the mesostructure and morphology of ethanebridged PMO materials synthesized under basic conditions. By using CTABr as the surfactant, the final PMO materials show a 2-D hexagonal (p6mm) mesophase, while PMO materials with cubic (Pm (3) over barn ) mesostructure are obtained when CTACl or CTA(SO4)(1)/(2) are used. With gradually replacing CTABr by CTACl or CTA(SO4) (1)/(2) while keeping the total surfactant concentration constant, a clear p6mm to Pm (3) over barn 3n mesophase evolution process is observed. For a given gel composition, the mesophase of ethanebridged PMO materials can also be adjusted by the addition of different sodium salts. In short, the effect of the counterions on the mesophase can be attributed to the binding strength of the ions on the surfactant micelles, which follows the Hofmeister series (SO42- < Cl- < Br-< NO3- < SCN-). Furthermore, it is found that the hydrolysis and condensation rate of the organosilica precursor also plays an important role in the formation of the final mesostructure

Abstract: A plasma enhanced-chemical vapor deposition (PE-CVD) route to Fe2O3-based materials on Al2O3(0001) single crystals at moderate growth temperatures (200-400 degrees C) is reported. The use of the fluorinated Fe(hfa)(2)TMEDA (hfa = 1,1,1,5,5,5-hexafluoro-2,4-pentanedionate; TMEDA = N,N,N',N'-tetramethylethylenediamine) molecular precursor in Ar/O-2 plasmas enabled an in situ F-doping of iron oxide matrices, with a fluorine content tunable as a function of the adopted preparative conditions. Variations of the thermal energy supply enabled control of the system phase composition, resulting in gamma-Fe2O3 at 200 degrees C and alpha-Fe2O3 nanostructures at higher deposition temperatures. Notably, at 400 degrees C the formation of highly oriented alpha-Fe2O3 nanocolumns characterized by an epitaxial relation with the Al2O3(0001) substrate was observed. Beside fluorine content, phase composition and nano-organization, even the system optical properties and, in particular, energy gap values, could be tailored by proper modifications of processing parameters.

Abstract: A new, single-step protocol for wrapping individual nanosized β-casein micelles with silica is presented. This biomolecule-friendly synthesis proceeds at low protein concentration at almost neutral pH, and makes use of sodium silicate instead of the common silicon alkoxides. This way, formation of potentially protein-denaturizing alcohols can be avoided. The pH of the citrate-buffered synthesis medium is close to the isoelectric point of β-casein, which favours micelle formation. A limited amount of sodium silicate is added to the protein micelle suspension, to form a thin silica coating around the β-casein micelles. The size distribution of the resulting proteinsilica structures was characterized using DLS and SAXS, as well as 1H NMR DOSY with a dedicated pulsed-field gradient cryo-probehead to cope with the low protein concentration. The degree of silica-condensation was investigated by 29Si MAS NMR, and the nanostructure was revealed by advanced electron microscopy techniques such as ESEM and HAADF-STEM. As indicated by the combined characterization results, a silica shell of 2 nm is formed around individual β-casein micelles giving rise to separate protein coresilica shell nanoparticles of 17 nm diameter. This alcohol-free method at mild temperature and pH is potentially suited for packing protein molecules into bio-compatible silica nanocapsules for a variety of applications in biosensing, therapeutic protein delivery and biocatalysis.

Abstract: Biomolecular self-assembly is an effective synthesis strategy for materials fabrication with unique structural complexity and properties. For the first time, we intergrate inner-particle mesoporosity in a three-dimensional (3D) interconnected macroporous TiO2 structure via the mediation of biomolecular self-assembly of the lipids and proteins from rape pollen coats and P123 to optimize the structure for high performance lithium storage. Benefitting from the hierarchically 3D interconnected macro-mesoporous structure with high surface area, small nanocrystallites and good electrolyte permeation, such unique porous structure demonstrates superior electrochemical performance, with high initial coulombic efficiency (94.4% at 1C) and a reversible discharge capacity of 161, 145, 127 and 97 mA h g-1 at 2, 5, 10 and 20C for 1000 cycles, with 79.3%, 89.9%, 90.1% and 87.4% capacity retention, respectively. Using SEM, TEM and HRTEM observations on the TiO2 materials before and after cycling, we verify that the inner-particle mesoporosity and the Li2Ti2O4 nanocrystallites formed during the cycling process in interconnected macroporous structure largely enhance the cycle life and rate performance. Our demonstration here offers opportunities towards developing and optimizing hierarchically porous structures for energy storage applications via biomolecular self-assembly.

Abstract: Pr2−xCexCuO4 (x = 0.05; 0.1; 0.15) samples were synthesized and systematically characterized towards application as a cathode material for solid oxide fuel cells (SOFCs). High-temperature electrical conductivity, thermal expansion, and electrocatalytic activity in the oxygen reduction reaction (ORR) were examined. The electrical conductivity of Pr2−xCexCuO4 oxides demonstrates semiconducting behavior up to 900 °C. Small Ce-doping (2.5 at%) allows an increase in electrical conductivity from 100 to 130 S cm−1 in air at 500–800 °C. DFT calculations revealed that the density of states directly below the Fermi level, comprised mainly of Cu 3d and O 2p states, is significantly affected by atoms in rare earth positions, which might give an indication of a correlation between calculated electronic structures and measured conducting properties. Ce-doping in Pr2−xCexCuO4 slightly increases TEC from 11.9 × 10−6 K−1 for x = 0 to 14.2 × 10−6 K−1 for x = 0.15. Substitution of 2.5% of Pr atoms in Pr2CuO4 by Ce is effective to enhance the electrochemical performance of the material as a SOFC cathode in the ORR (ASR of Pr1.95Ce0.05CuO4 electrode applied on Ce0.9Gd0.1O1.95 electrolyte is 0.39 Ω cm2 at 750 °C in air). The peak power density achieved for the electrolyte-supported fuel cell with the Pr1.95Ce0.05CuO4 cathode is 150 mW cm−2 at 800 °C

Abstract: A superior field electron emission (FEE) source made from a hierarchical heterostructure, where two-dimensional hexagonal boron nitride (hBN) nanowalls were coated on one-dimensional diamond nanorods (DNRs), is fabricated using a simple and scalable method. FEE characteristics of hBN-DNR display a low turn-on field of 6.0 V mu m(-1), a high field enhancement factor of 5870 and a high life-time stability of 435 min. Such an enhancement in the FEE properties of hBN-DNR derives from the distinctive material combination, i.e., high aspect ratio of the heterostructure, good electron transport from the DNR to the hBN nanowalls and efficient field emission of electrons from the hBN nanowalls. The prospective application of these heterostructures is further evidenced by enhanced microplasma devices using hBN-DNR as a cathode, in which the threshold voltage was lowered to 350 V, affirming the role of hBN-DNR in the improvement of electron emission.

Abstract: Epitaxial integration of transition-metal oxides with silicon brings a variety of functional properties to the well-established platform of electronic components. In this process, deoxidation and passivation of the silicon surface are one of the most important steps, which in our study were controlled by an ultra-thin layer of SrO and monitored by using transmission electron microscopy (TEM), electron energy-loss spectroscopy (EELS), synchrotron X-ray diffraction (XRD) and reflection high energy electron diffraction (RHEED) methods. Results revealed that an insufficient amount of SrO leads to uneven deoxidation of the silicon surface<italic>i.e.</italic>formation of pits and islands, whereas the composition of the as-formed heterostructure gradually changes from strontium silicide at the interface with silicon, to strontium silicate and SrO in the topmost layer. Epitaxial ordering of SrO, occurring simultaneously with silicon deoxidation, was observed. RHEED analysis has identified that SrO is epitaxially aligned with the (001) Si substrate both with SrO (001) and SrO (111) out-of-plane directions. This observation was discussed from the point of view of SrO desorption, SrO-induced deoxidation of the Si (001) surface and other interfacial reactions as well as structural ordering of deposited SrO. Results of the study present an important milestone in understanding subsequent epitaxial integration of functional oxides with silicon using SrO.

Abstract: We present KITE, a general purpose open-source tight-binding software for accurate real-space simulations of electronic structure and quantum transport properties of large-scale molecular and condensed systems with tens of billions of atomic orbitals (N similar to 10(10)). KITE's core is written in C++, with a versatile Python-based interface, and is fully optimized for shared memory multi-node CPU architectures, thus scalable, efficient and fast. At the core of KITE is a seamless spectral expansion of lattice Green's functions, which enables large-scale calculations of generic target functions with uniform convergence and fine control over energy resolution. Several functionalities are demonstrated, ranging from simulations of local density of states and photo-emission spectroscopy of disordered materials to large-scale computations of optical conductivity tensors and real-space wave-packet propagation in the presence of magneto-static fields and spin-orbit coupling. On-the-fly calculations of real-space Green's functions are carried out with an efficient domain decomposition technique, allowing KITE to achieve nearly ideal linear scaling in its multi-threading performance. Crystalline defects and disorder, including vacancies, adsorbates and charged impurity centres, can be easily set up with KITE's intuitive interface, paving the way to user-friendly large-scale quantum simulations of equilibrium and non-equilibrium properties of molecules, disordered crystals and heterostructures subject to a variety of perturbations and external conditions.

Abstract: The interest in 2-dimensional systems with a honeycomb lattice and related Dirac-­type electronic bands has exceeded the prototype graphene1. Currently, 2-­dimensional atomic2,3 and nanoscale4-­8 systems are extensively investigated in the search for materials with novel electronic properties that can be tailored by geometry. The immediate question that arises is how to fabricate 2-­D semiconductors that have a honeycomb nanogeometry, and as a consequence of that, display a Dirac-­type band structure? Here, we show that atomically coherent honeycomb superlattices of rocksalt (PbSe, PbTe) and zincblende (CdSe, CdTe) semiconductors can be obtained by nanocrystal self-­assembly and facet-­to-­facet atomic bonding, and subsequent cation exchange. We present a extended structural analysis of atomically coherent 2-­D honeycomb structures that were recently obtained with self-assembly and facet-­to-­facet bonding9. We show that this process may in principle lead to three different types of honeycomb structures, one with a graphene type-­, and two others with a silicene-­type structure. Using TEM, electron diffraction, STM and GISAXS it is convincingly shown that the structures are from the silicene-­type. In the second part of this work, we describe the electronic structure of graphene-­type and silicene type honeycomb semiconductors. We present the results of advanced electronic structure calculations using the sp3d5s* atomistic tight-­binding method10. For simplicity, we focus on semiconductors with a simple and single conduction band for the native bulk semiconductor. When the 3-­D geometry is changed into 2-­D honeycomb, a conduction band structure transformation to two types of Dirac cones, one for S-­ and one for P-­orbitals, is observed. The width of the bands depends on the honeycomb period and the coupling between the nanocrystals. Furthermore, there is a dispersionless P-­orbital band, which also forms a landmark of the honeycomb structure. The effects of considerable intrinsic spin-­orbit coupling are briefly considered. For heavy-­element compounds such as CdTe, strong intrinsic spin-­‐orbit coupling opens a non-­trivial gap at the P-­orbital Dirac point, leading to a quantum Spin Hall effect10-­12. Our work shows that well known semiconductor crystals, known for centuries, can lead to systems with entirely new electronic properties, by the simple action of nanogeometry. It can be foreseen that such structures will play a key role in future opto-­electronic applications, provided that they can be fabricated in a straightforward way.

Abstract: Amyloid fibrils, which are closely associated with various neurodegenerative
diseases, are the final products in many protein aggregation pathways. The identification of fibrils at low concentration is, therefore, pivotal in disease diagnosis and development of therapeutic strategies. We report a methodology for the specific identification of amyloid fibrils using chiroptical effects in plasmonic nanoparticles. The formation of amyloid fibrils based on α-synuclein was probed using gold nanorods, which showed no
apparent interaction with monomeric proteins but effective adsorption onto fibril structures via noncovalent interactions. The amyloid structure drives a helical nanorod arrangement, resulting in intense optical activity at the surface plasmon resonance wavelengths. This sensing technique was successfully applied to human brain homogenates of patients affected by Parkinson’s disease,
wherein protein fibrils related to the disease were identified through chiral signals from Au nanorods in the visible and near IR, whereas healthy brain samples did not exhibit any meaningful optical activity. The technique was additionally extended to the specific detection of infectious amyloids formed by prion proteins, thereby confirming the wide potential of the technique. The intense chiral response driven by strong dipolar coupling in helical Au nanorod arrangements allowed us to detect amyloid fibrils down to nanomolar concentrations.

Abstract: We present a computational imaging mode for large scale electron microscopy data, which retrieves a complex wave from noisy/sparse intensity recordings using a deep learning approach and subsequently reconstructs an image of the specimen from the Convolutional Neural Network (CNN) predicted exit waves. We demonstrate that an appropriate forward model in combination with open data frameworks can be used to generate large synthetic datasets for training. In combination with augmenting the data with Poisson noise corresponding to varying dose-values, we effectively eliminate overfitting issues. The U-NET[1] based architecture of the CNN is adapted to the task at hand and performs well while maintaining a relatively small size and fast performance. The validity of the approach is confirmed by comparing the reconstruction to well-established methods using simulated, as well as real electron microscopy data. The proposed method is shown to be effective particularly in the low dose range, evident by strong suppression of noise, good spatial resolution, and sensitivity to different atom types, enabling the simultaneous visualisation of light and heavy elements and making different atomic species distinguishable. Since the method acts on a very local scale and is comparatively fast it bears the potential to be used for near-real-time reconstruction during data acquisition.

Abstract: Organic and biological compounds (especially those related to the pharmaceutical industry) have always been of great interest for researchers due to their importance for the development of new drugs to diagnose, cure, treat or prevent disease. As many new API (active pharmaceutical ingredients) and their polymorphs are in nanocrystalline or in amorphous form blended with amorphous polymeric matrix (known as amorphous solid dispersion—ASD), their structural identification and characterization at nm scale with conventional X-Ray/Raman/IR techniques becomes difficult. During any API synthesis/production or in the formulated drug product, impurities must be identified and characterized. Electron energy loss spectroscopy (EELS) at high energy resolution by transmission electron microscope (TEM) is expected to be a promising technique to screen and identify the different (organic) compounds used in a typical pharmaceutical or biological system and to detect any impurities present, if any, during the synthesis or formulation process. In this work, we propose the use of monochromated TEM-EELS, to analyze selected peptides and organic compounds and their polymorphs. In order to validate EELS for fingerprinting (in low loss/optical region) and by further correlation with advanced DFT, simulations were utilized.