Abstract: This study reports the low temperature and low pressure conversion (up to 160 °C, p = 3.5 bar) of CO2 and H2 to CO using plasmonic Au/TiO2 nanocatalysts and mildly concentrated artificial sunlight as the sole energy source (up to 13.9 kW·m-2 = 13.9 suns). To distinguish between photothermal and non-thermal contributors, we investigated the impact of the Au nanoparticle size and light intensity on the activity and selectivity of the catalyst. A comparative study between P25 TiO2-supported Au nanocatalysts of a size of 6 nm and 16 nm displayed a 15 times higher activity for the smaller particles, which can only partially be attributed to the higher Au surface area. Other factors that may play a role are e.g., the electronic contact between Au and TiO2 and the ratio between plasmonic absorption and scattering. Both catalysts displayed ≥84% selectivity for CO (side product is CH4). Furthermore, we demonstrated that the catalytic activity of Au/TiO2 increases exponentially with increasing light intensity, which indicated the presence of a photothermal contributor. In dark, however, both Au/TiO2 catalysts solely produced CH4 at the same catalyst bed temperature (160 °C). We propose that the difference in selectivity is caused by the promotion of CO desorption through charge transfer of plasmon generated charges (as a non-thermal contributor).

Abstract: Asymmetric dye molecules have unusual optical and electronic properties1, 2, 3. For instance, they show a strong second-order nonlinear optical (NLO) response that has attracted great interest for potential applications in electro-optic modulators for optical telecommunications and in wavelength conversion of lasers2, 3. However, the strong Coulombic interaction between the large dipole moments of these molecules favours a pairwise antiparallel alignment that cancels out the NLO response when incorporated into bulk materials. Here, we show that by including an elongated dipolar dye (p,p′-dimethylaminonitrostilbene, DANS, a prototypical asymmetric dye with a strong NLO response4) inside single-walled carbon nanotubes (SWCNTs)5, 6, an ideal head-to-tail alignment in which all electric dipoles point in the same sense is naturally created. We have applied this concept to synthesize solution-processible DANS-filled SWCNTs that show an extremely large total dipole moment and static hyperpolarizability (β0 = 9,800 × 10−30 e.s.u.), resulting from the coherent alignment of arrays of ∼70 DANS molecules.

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: Electron tomography is currently a versatile tool to investigate the connection between the structure and properties of nanomaterials. However, a quantitative interpretation of electron tomography results is still far from straightforward. Especially accurate quantification of pore-space is hampered by artifacts introduced in all steps of the processing chain, i.e., acquisition, reconstruction, segmentation and quantification. Furthermore, most common approaches require subjective manual user input. In this paper, the PORES algorithm POre REconstruction and Segmentation is introduced; it is a tailor-made, integral approach, for the reconstruction, segmentation, and quantification of porous nanomaterials. The PORES processing chain starts by calculating a reconstruction with a nanoporous-specific reconstruction algorithm: the Simultaneous Update of Pore Pixels by iterative REconstruction and Simple Segmentation algorithm (SUPPRESS). It classifies the interior region to the pores during reconstruction, while reconstructing the remaining region by reducing the error with respect to the acquired electron microscopy data. The SUPPRESS reconstruction can be directly plugged into the remaining processing chain of the PORES algorithm, resulting in accurate individual pore quantification and full sample pore statistics. The proposed approach was extensively validated on both simulated and experimental data, indicating its ability to generate accurate statistics of nanoporous materials.

Abstract: Electron tomography is an essential imaging technique for the investigation of morphology and 3D structure of nanomaterials. This method, however, suffers from well-known missing wedge artifacts due to a restricted tilt range, which limits the objectiveness, repeatability and efficiency of quantitative structural analysis. Discrete tomography represents one of the promising reconstruction techniques for materials science, potentially capable of delivering higher fidelity reconstructions by exploiting the prior knowledge of the limited number of material compositions in a specimen. However, the application of discrete tomography to practical datasets remains a difficult task due to the underlying challenging mathematical problem. In practice, it is often hard to obtain consistent reconstructions from experimental datasets. In addition, numerous parameters need to be tuned manually, which can lead to bias and non-repeatability. In this paper, we present the application of a new
iterative reconstruction technique, named TVR-DART, for discrete electron tomography. The technique is capable of consistently delivering reconstructions with significantly reduced missing wedge artifacts for a variety of challenging data and imaging conditions, and can automatically estimate its key parameters. We describe the principles of the technique and apply it to datasets from three different types of samples acquired under diverse imaging modes. By further reducing the available tilt range and number of projections, we show that the
proposed technique can still produce consistent reconstructions with minimized missing wedge artifacts. This new development promises to provide the electron microscopy community with an easy-to-use and robust tool for high-fidelity 3D characterization of nanomaterials.