Abstract: Gold nanorods (Au NRs) are an exceptionally promising tool in nanotechnology due to three key factors: (i) their strong interaction with electromagnetic radiation, stemming from their plasmonic nature, (ii) the ease with which the resonance frequency of their longitudinal plasmon mode can be tuned from the visible to the near-infrared region of the electromagnetic spect r u m based on their aspect ratio, and (iii) their simple and cost-effective preparation through seed-mediated chemical growth. In this synthetic method, surfactants play a critical role in controlling the size, shape, and colloidal stabi l i t y of Au NRs. For example, surfactants can stabilize specific crystallographic facets during the formation of Au NRs, leading to t h e formation of NRs with specific morphologies. The process of surfactant adsorption onto the NR surface may result in various assemblies of surfactant molecules, such as spherical micelles, elongated micelles, or bilayers. Again, the assembly mode is critical toward determining the further availabi l i t y of the Au NR surface to the surrounding medium. Despite its importance and a great deal of research effort, the interaction between Au NPs and surfactants remains insufficiently understood, because the assembly process is influenced by numerous factors, including the chemical nature of the surfactant, the surface morphology of Au NPs, and solution parameters. Therefore, gaining a more comprehensive understanding of these interactions is essential to unlock the full potential of the seed-mediated growth method and the applications of plasmonic NPs. A plethora of characterization techniques have been applied to reach such an understanding , but many open questions remain. In this Account, we review the current knowledge on the interactions between surfactants and Au NRs. We briefly introduce the state-of-the-art methods for synthesizing Au NRs and highlight the crucial role of cationic surfactants during this process. The self-assembly and organization of surfactants on the Au NR surface is then discussed to better understand their role in seed-mediated growth. Subsequently, we provide examples and elucidate how chemical additives can be used to modulate micellar assemblies, in turn allowing for a finer control over the growth of Au NRs, including chiral NRs. Next, we review the main experimental characterization and computational modeling techniques that have been applied to shed light on the arrangement of surfactants on Au NRs and summarize the advantages and disadvantages for each technique. The Account ends with a “Conclusions and Outlook” section, outlining promising future research directions and developments that we consider are sti l l required, mostly related to the application of electron microscopy in liquid and in 3D. Finally, we remark on the potential of exploiting machine learning techniques to predict synthetic routes for NPs with predefined structures and properties.

Abstract: Despite the natural abundance and promising properties of Si, there are few examples of crystalline Si-based catalysts. Here, the authors report an epitaxial growth method to construct Co single atoms on Si for light driven CO2 reduction to syngas. Improving the dispersion of active sites simultaneous with the efficient harvest of photons is a key priority for photocatalysis. Crystalline silicon is abundant on Earth and has a suitable bandgap. However, silicon-based photocatalysts combined with metal elements has proved challenging due to silicon's rigid crystal structure and high formation energy. Here we report a solid-state chemistry that produces crystalline silicon with well-dispersed Co atoms. Isolated Co sites in silicon are obtained through the in-situ formation of CoSi2 intermediate nanodomains that function as seeds, leading to the production of Co-incorporating silicon nanocrystals at the CoSi2/Si epitaxial interface. As a result, cobalt-on-silicon single-atom catalysts achieve an external quantum efficiency of 10% for CO2-to-syngas conversion, with CO and H-2 yields of 4.7 mol g((Co))(-1) and 4.4 mol g((Co))(-1), respectively. Moreover, the H-2/CO ratio is tunable between 0.8 and 2. This photocatalyst also achieves a corresponding turnover number of 2 x 10(4) for visible-light-driven CO2 reduction over 6 h, which is over ten times higher than previously reported single-atom photocatalysts.

Abstract: Nanoplatelets offer many possibilities to construct advanced materials due to new properties associated with their (semi)two-dimensional shapes. However, precise control of both positional and orientational order of the nanoplatelets in three dimensions, which is required to achieve emerging and collective properties, is challenging to realize. Here, we combine experiments, advanced electron tomography and computer simulations to explore the structure of supraparticles self-assembled from nanoplatelets in slowly drying emulsion droplets. We demonstrate that the rich phase behaviour of nanoplatelets, and its sensitivity to subtle changes in shape and interaction potential can be used to guide the self-assembly into a wide range of different structures, offering precise control over both orientation and position order of the nanoplatelets. Our research is expected to shed light on the design of hierarchically structured metamaterials with distinct shape- and orientation- dependent properties. Nanoplatelets can be used as anisotropic building blocks for constructing novel optoelectronic materials. Here, Wang et al. show a route of assembling nanoplatelets with controllable positional and orientational order in three dimensions facilitated by the surface tension of drying emulsion droplets.

Abstract: 3D characterization of assemblies of nanoparticles is of great importance to determine their structure-property connection. Such investigations become increasingly more challenging when the assemblies become larger and more compact. In this paper, we propose an optimized approach for electron tomography to minimize artefacts related to beam broadening in High Angle Annular Dark-Field Scanning Transmission Electron Microscopy mode. These artefacts are typically present at one side of the reconstructed 3D data set for thick nanoparticle assemblies. To overcome this problem, we propose a procedure in which two tomographic tilt series of the same sample are acquired. After acquiring the first series, the sample is flipped over 180o, and a second tilt series is acquired. By merging the two reconstructions, blurring in the reconstructed volume is minimized. Next, this approach is combined with an advanced three-dimensional reconstruction algorithm yielding quantitative structural information. Here, the approach is applied to a thick and compact assembly of spherical Au nanoparticles, but the methodology can we used to investigate a broad range of samples.

Abstract: 3D real-space analysis of thick nanoparticle crystals is non-trivial. Here, the authors demonstrate the structural analysis of a bulk-like Laves phase by imaging an off-stoichiometric binary mixture of hard-sphere-like nanoparticles in spherical confinement by electron tomography, enabling defect analysis on the single-particle level. Assembling binary mixtures of nanoparticles into crystals, gives rise to collective properties depending on the crystal structure and the individual properties of both species. However, quantitative 3D real-space analysis of binary colloidal crystals with a thickness of more than 10 layers of particles has rarely been performed. Here we demonstrate that an excess of one species in the binary nanoparticle mixture suppresses the formation of icosahedral order in the self-assembly in droplets, allowing the study of bulk-like binary crystal structures with a spherical morphology also called supraparticles. As example of the approach, we show single-particle level analysis of over 50 layers of Laves phase binary crystals of hard-sphere-like nanoparticles using electron tomography. We observe a crystalline lattice composed of a random mixture of the Laves phases. The number ratio of the binary species in the crystal lattice matches that of a perfect Laves crystal. Our methodology can be applied to study the structure of a broad range of binary crystals, giving insights into the structure formation mechanisms and structure-property relations of nanomaterials.

Abstract: Colloidal nanoparticles (NPs) including nanowires and nanosheets made by chemical methods involve many organic ligands. When the structure of NPs is investigated via transmission electron microscopy (TEM), the organic ligands act as a source for e-beam induced deposition and this causes substantial build-up of carbon layers in the investigated areas, which is typically referred to as “contamination” in the eld of electron mi- croscopy. This contamination is often more severe for scanning TEM, a technique that is based on a focused electron beam and hence higher electron dose rate. In this paper, we report a simple and effective method to clean drop-cast TEM grids that contain NPs with ligands. Using a combination of activated carbon and ethanol, this method effectively reduces the amount of ligands on TEM grids, and therefore greatly improves the quality of electron microscopy images and subsequent analytical measurements. This ef cient and facile method can be helpful during electron microscopy investigation of different kinds of nanomaterials that suffer from ligand- induced contamination.

Abstract: The influence of geometry on the local and global packing of particles is important to many fundamental and applied research themes, such as the structure and stability of liquids, crystals and glasses. Here we show by experiments and simulations that a binary mixture of hard-sphere-like nanoparticles crystallizing into a MgZn(2)Laves phase in bulk spontaneously forms icosahedral clusters in slowly drying droplets. Using advanced electron tomography, we are able to obtain the real-space coordinates of all the spheres in the icosahedral clusters of up to about 10,000 particles. The local structure of 70-80% of the particles became similar to that of the MgCu(2)Laves phase. These observations are important for photonic applications. In addition, we observed in simulations that the icosahedral clusters nucleated away from the spherical boundary, which is distinctly different from that of the single species clusters. Our findings open the way for particle-level studies of nucleation and growth of icosahedral clusters, and of binary crystallization. The authors investigate out-of-equilibrium crystallization of a binary mixture of sphere-like nanoparticles in small droplets. They observe the spontaneous formation of an icosahedral structure with stable MgCu(2)phases, which are promising for photonic applications.

Abstract: Substitutional doping is a potentially powerful technique to control the properties of nanocrystal (NC) superlattices (SLs). However, not every NC can be substituted into any lattice, as the NCs have to be close in size and shape, limiting the application of substitutional doping. Here we show that this limitation can be overcome by employing ligands of various size. We show that small NCs with long ligands can be substituted into SLs of big NCs with short ligands. Furthermore, we show that shape differences can also be overcome and that cubes can substitute spheres when both are coated with long ligands. Finally, we use the NC effective ligand size, softness, and effective overall size ratio to explain observed doping behaviors.

Abstract: Hydrogenotrophic denitrification is a novel and sustainable process for nitrogen removal, which utilizes hydrogen as electron donor, and carbon dioxide as carbon source. Recent studies have shown that nitrous oxide (N2O), a highly undesirable intermediate and potent greenhouse gas, can accumulate during this process. In this work, a new mathematical model is developed to describe nitrogen oxides dynamics, especially N2O, during hydrogenotrophic denitrification for the first time. The model describes electron competition among the four steps of hydrogenotrophic denitrification through decoupling hydrogen oxidation and nitrogen reduction processes using electron carriers, in contrast to the existing models that couple these two processes and also do not consider N2O accumulation. The developed model satisfactorily describes experimental data on nitrogen oxides dynamics obtained from two independent hydrogenotrophic denitrifying cultures under various hydrogen and nitrogen oxides supplying conditions, suggesting the validity and applicability of the model. The results indicated that N2O accumulation would not be intensified under hydrogen limiting conditions, due to the higher electron competition capacity of N2O reduction in comparison to nitrate and nitrite reduction during hydrogenotrophic denitrification. The model is expected to enhance our understanding of the process during hydrogenotrophic denitrification and the ability to predict N2O accumulation.

Abstract: The mobilization of arsenic (As) in aquatic environment (groundwater) can cause severe environmental and healthy issues. To develop remediation strategies, we proposed a comprehensive mathematical model to describe the As removal in a arsenite (As (III)) oxidizing and ferrous iron (Fe (II)) oxidizing denitrifying granular biofilm system. In the model framework, the growth-linked microbial oxidation of As (III) and Fe (II) was coupled to chemolithotrophic denitrification of one-step reduction of nitrate to nitrogen gas. Meanwhile, the precipitation of ferric iron (Fe (III)) and adsorption of arsenate (As (V)) onto the biogenic Fe (III) (hydr)oxides were also considered. The model was calibrated by comparing the model predictions against experimental data from batch experiments. The validity of the model was further demonstrated through testing against long-term experimental results from five independent bioreactors with different reactor configurations and operational conditions. Modeling results revealed that the granule size would exert a limited impact on arsenic and iron removal. Nevertheless, their removal efficiencies increased rapidly with the increase of hydraulic retention time (HRT) from 1 h to 12 h, but became independent of HRT as it further increased. The established model framework enables interpretation of a range of experimental observations on As and Fe removal and helps to identify the optimal conditions for enhanced arsenic remediation. (C) 2017 Elsevier Ltd. All rights reserved.

Abstract: In this work, a mathematical model was developed to describe the dynamics of fermentation products in sludge alkaline fermentation systems for the first time. In this model, the impacts of alkaline fermentation on sludge disintegration, hydrolysis, acidogenesis, acetogenesis, and methanogenesis processes are specifically considered for describing the high-level formation of fermentation products. The model proposed successfully reproduced the experimental data obtained from five independent sludge alkaline fermentation studies. The modeling results showed that alkaline fermentation largely facilitated the disintegration, acidogenesis, and acetogenesis processes and severely inhibited methanogenesis process. With the pH increase from 7.0 to 10.0, the disintegration, acidogenesis, and acetogenesis processes respectively increased by 53%, 1030%, and 30% while methane production decreased by 3800%.However, no substantial effect on hydrolysis process was found. The model also indicated that the pathway of acetoclastic methanogenesis was more severely inhibited by alkaline condition than that of hydrogentrophic methanogenesis. (C) 2017 Elsevier Ltd. All rights reserved.