Abstract: We show here that thermal treatment of small seeds results in extensive twinning and a subsequent drastic yield improvement (>85%) in the formation of pentatwinned nanoparticles, with pre-selected morphology (nanorods, bipyramids and decahedra) and aspect ratio. The “quality” of the seeds thus defines the yield of the obtained nanoparticles, which in the case of nanorods avoids the need for additives such as Ag+ ions. This modified seeded growth method also improves reproducibility, as the seeds can be stored for extended periods of time without compromising the quality of the final nanoparticles. Additionally, minor modification of the seeds with Pd allows their localization within the final particles, which opens new avenues toward mechanistic studies. All together, these results represent a paradigm shift in anisotropic gold nanoparticle synthesis.

Abstract: We have developed a general protocol for the preparation of hybrid nanostructures formed by nanoparticles (NPs) of molecule-based magnets based on Prussian Blue Analogues (PBAs) decorated with plasmonic Au NPs of different shapes. By adjusting the pH, Au NPs can be attached preferentially along the edges of the PBA or randomly on the surface. The protocol allows tuning the plasmonic properties of the hybrids in the whole visible spectrum.

Abstract: A broad range of cationic nonstoichiometry has been demonstratedfor the Li-rich layered rock-salt-type oxide Li2MoO3, which has generally been considered as a phase with a well-defined chemical composition. Li2+xMo1-xO3(-0.037 <= x <= 0.124) solid solutions were synthesized via hydrogen reduction ofLi2MoO4in the temperature range of 650-1100 degrees C, withxdecreasing with theincrease of the reduction temperature. The solid solutions adopt a monoclinicallydistorted O3-type layered average structure and demonstrate a robust localordering of the Li cations and Mo3triangular clusters within the mixed Li/Mocationic layers. The local structure was scrutinized in detail by electron diffractionand aberration-corrected scanning transmission electron microcopy (STEM),resulting in an ordering model comprising a uniform distribution of the Mo3clusters compatible with local electroneutrality and chemical composition. The geometry of the triangular clusters with their oxygenenvironment (Mo3O13groups) has been directly visualized using differential phase contrast STEM imaging. The established localstructure was used as input for density functional theory (DFT)-based calculations; they support the proposed atomic arrangementand provide a plausible explanation for the staircase galvanostatic charge profiles upon electrochemical Li+extraction fromLi2+xMo1-xO3in Li cells. According to DFT, all electrochemical capacity in Li2+xMo1-xO3solely originates from the cationic Moredox process, which proceeds via oxidation of the Mo3triangular clusters into bent Mo3chains where the electronic capacity of the clusters depends on the initial chemical composition and Mo oxidation state defining the width of the first charge low-voltageplateau. Further oxidation at the high-voltage plateau proceeds through decomposition of the Mo3chains into Mo2dimers and further into individual Mo6+cations

Abstract: Nanorattles are metallic core–shell particles with core and shell separated by a dielectric spacer. These
nanorattles have been identified as a promising class of nanoparticles, due to their extraordinary high
electric-field enhancement inside the cavity. Limiting factors are reproducibility and loss of axial symmetry
owing to the movable metal core; movement of the core results in fluctuation of the nanocavity dimensions
and commensurate variations in enhancement factor. We present a novel synthetic approach for
the robust fixation of the central gold rod within a well-defined box, which results in an axisymmetric
nanorattle. We determine the structure of the resulting axisymmetric nanorattles by advanced transmission
electron microscopy (TEM) and small-angle X-ray scattering (SAXS). Optical absorption and scattering
cross-sections obtained from UV-vis-NIR spectroscopy quantitatively agree with finite-difference
time-domain (FDTD) simulations based on the structural model derived from SAXS. The predictions of
high and homogenous field enhancement are evidenced by scanning TEM electron energy loss spectroscopy
(STEM-EELS) measurement on single-particle level. Thus, comprehensive understanding of
structural and optical properties is achieved for this class of nanoparticles, paving the way for photonic
applications where a defined and robust unit cell is crucial.

Abstract: Studying protein interactions is of vital importance both to fundamental biology research and to medical applications. Here, we report on the experimental proof of a universally applicable label-free homogeneous platform for rapid protein analysis. It is based on optically detecting changes in the rotational dynamics of magnetically agitated core-shell nanorods upon their specific interaction with proteins. By adjusting the excitation frequency, we are able to optimize the measurement signal for each analyte protein size. In addition, due to the locking of the optical signal to the magnetic excitation frequency, background signals are suppressed, thus allowing exclusive studies of processes at the nanoprobe surface only. We study target proteins (soluble domain of the human epidermal growth factor receptor 2 – sHER2) specifically binding to antibodies (trastuzumab) immobilized on the surface of our nanoprobes and demonstrate direct deduction of their respective sizes. Additionally, we examine the dependence of our measurement signal on the concentration of the analyte protein, and deduce a minimally detectable sHER2 concentration of 440 pM. For our homogeneous measurement platform, good dispersion stability of the applied nanoprobes under physiological conditions is of vital importance. To that end, we support our measurement data by theoretical modeling of the total particle-particle interaction energies. The successful implementation of our platform offers scope for applications in biomarker-based diagnostics as well as for answering basic biology questions.

Abstract: Characterization of core-shell type nanoparticles in 3D by transmission electron microscopy (TEM) can be very challenging. Especially when both heavy and light elements co-exist within the same nanostructure, artefacts in the 3D reconstruction are often present. A representative example would be a particle comprising an anisotropic metallic (Au) nanoparticle coated with a (mesoporous) silica shell. To obtain a reliable 3D characterization of such an object, we propose a dose-efficient strategy to simultaneously acquire high angle annular dark field scanning TEM and annular dark field tilt series for tomography. The 3D reconstruction is further improved by applying an advanced masking and interpolation approach to the acquired data. This new methodology enables us to obtain high quality reconstructions from which also quantitative information can be extracted. This approach is broadly applicable to investigate hybrid core-shell materials.

Abstract: The microstructural complexity of Li-rich cathode materials has so far hampered understanding the critical link between size, morphology and structural defects with both capacity and voltage fadings that this family of materials exhibits. Li2MnO3 is used here as a model material to extract reliable structure–property
relationships that can be further exploited for the development of high-performing and long-lasting Li-rich oxides. A series of samples with microstructural variability have been prepared and thoroughly characterized using the FAULTS software, which allows quantification of planar defects and extraction of
average crystallite sizes. Together with transmission electron microscopy (TEM) and density functional theory (DFT) results, the successful application of FAULTS analysis to Li2MnO3 has allowed rationalizing the synthesis conditions and identifying the individual impact of concurrent microstructural features on
both voltage and capacity fadings, a necessary step for the development of high-capacity Li-ion cathode materials with enhanced cycle life.

Abstract: Anisotropic bimetallic nanoparticles are promising candidates for plasmonic and catalytic applications. Their catalytic performance and plasmonic properties are closely linked to the distribution of the two metals, which can change during applications in which the particles are exposed to heat. Due to this fact, correlating the thermal stability of complex heterogeneous nanoparticles to their microstructural properties is of high interest for the practical applications of such materials. Here, we employ quantitative electron tomography in high-angle annular dark-field scanning transmission electron microscopy (HAADFSTEM) mode to measure the 3D elemental diffusion dynamics in individual anisotropic Au−Ag nanoparticles upon heating in situ. This approach allows us to study the elemental redistribution in complex, asymmetric nanoparticles on a single particle level, which has been inaccessible to other techniques so far. In this work, we apply the proposed method to compare the alloying dynamics of Au−Ag nanoparticles with different shapes and compositions and find that the shape of the nanoparticle does not exhibit a significant effect on the alloying speed whereas the composition does. Finally, comparing the experimental results to diffusion simulations allows us to estimate the diffusion coefficients of the metals for individual nanoparticles.

Abstract: The combination of energy-dispersive X-ray spectroscopy (EDX) and electron tomography is a powerful approach to retrieve the 3D elemental distribution in nanomaterials, providing an unprecedented level of information for complex, multi-component systems, such as semiconductor devices, as well as catalytic and plasmonic nanoparticles. Unfortunately, the applicability of EDX tomography is severely limited because of extremely long acquisition times and high electron irradiation doses required to obtain 3D EDX reconstructions with an adequate signal-to-noise ratio. One possibility to address this limitation is intelligent denoising of experimental data using prior expectations about the objects of interest. Herein, this approach is followed using the deep learning methodology, which currently demonstrates state-of-the-art performance for an increasing number of data processing problems. Design choices for the denoising approach and training data are discussed with a focus on nanoparticle-like objects and extremely noisy signals typical for EDX experiments. Quantitative analysis of the proposed method demonstrates its significantly enhanced performance in comparison to classical denoising approaches. This allows for improving the tradeoff between the reconstruction quality, acquisition time and radiation dose for EDX tomography. The proposed method is therefore especially beneficial for the 3D EDX investigation of electron beam-sensitive materials and studies of nanoparticle transformations.

Abstract: In this study the effects of the heating rate and heating time on the formation of crystal-like benzene bridged periodic mesoporous organosilicas (PMOs) are investigated. The time needed to heat up an autoclave during the hydrothermal treatment has shown to be crucial in the synthesis of PMOs, while the total duration of heating gave rise to only minor differences. By choosing a smart heating profile, superior PMO materials can be obtained in a short time. Different heating profiles in a range from one minute to one hour are adopted by microwave equipment and compared with conventional heating methods. The heating rate has a large influence on the porosity characteristics and the uniformity of the obtained particles. Moreover, two new alternative synthetic strategies to adopt the smart heating profile are presented, in order to give some possible solutions for the expensive microwave equipment.

Abstract: Branched plasmonic nanocrystals (NCs) have attracted much attention due to electric field enhancements at their tips. Seeded growth provides routes to NCs with defined branching patterns and, in turn, near‐field distributions with defined symmetries. Here, a systematic analysis was undertaken in which seeds containing different distributions of planar defects were used to grow branched NCs in order to understand how their distributions direct the branching. Characterization of the products by multimode electron tomography and analysis of the NC morphologies at different overgrowth stages indicate that the branching patterns are directed by the seed defects, with the emergence of branches from the seed faces consistent with minimizing volumetric strain energy at the expense of surface energy. These results contrast with growth of branched NCs from single‐crystalline seeds and provide a new platform for the synthesis of symmetrically branched plasmonic NCs.

Abstract: Chemically synthesized metal nanoparticles with morphological chiral features are known to exhibit strong circular dichroism. However, we still lack understanding of the correlation between morphological and chiroptical features of plasmonic nanoparticles. To shed light on that question, single nanoparticle experiments are required. We performed photothermal circular dichroism measurements of single chiral and achiral gold nanoparticles and correlated the chiroptical response to the 3D morphology of the same nanoparticles retrieved by electron tomography. In contrast to an ensemble measurement, we show that individual particles within the ensemble display a broad distribution of strength and handedness of circular dichroism signals. Whereas obvious structural chiral features, such as helical wrinkles, translate into chiroptical ones, nanoparticles with less obvious chiral morphological features can also display strong circular dichroism signals. Interestingly, we find that even seemingly achiral nanoparticles can display large g-factors. The origin of this circular dichroism signal is discussed in terms of plasmonics and other potentially relevant factors.

Abstract: A series of heterogeneous catalysts consisting of highly dispersed Pt nanoparticles supported on nanosized ZrO2 (20 to 60 nm) was synthesized and investigated for the one-pot transfer hydrogenation between glycerol and cyclohexene to produce lactic acid and cyclohexane, without any additional H-2. Different preparation methods were screened, by varying the calcination and reduction procedures with the purpose of optimizing the dispersion of Pt species (i.e., as single-atom sites or extra-fine Pt nanoparticles) on the ZrO2 support. The Pt/ZrO2 catalysts were characterized by means of transmission electron microscopy techniques (HAADF-STEM, TEM), elemental analysis (ICP-OES, EDX mapping), N-2-physisorption, H-2 temperature-programmed-reduction (H-2-TPR), X-ray photoelectron spectroscopy (XPS), and X-ray diffraction (XRD). Based on this combination of techniques it was possible to correlate the temperature of the calcination and reduction treatments with the nature of the Pt species. The best catalyst consisted of subnanometer Pt clusters (<1 nm) and atomically dispersed Pt (as Pt2+ and Pt4+) on the ZrO2 support, which were converted into extra-fine Pt nanoparticles (average size = 1.4 nm) upon reduction. These nanoparticles acted as catalytic species for the transfer hydrogenation of glycerol with cyclohexene, which gave an unsurpassed 95% yield of lactic acid salt at 96% glycerol conversion (aqueous glycerol solution, NaOH as promoter, 160 degrees C, 4.5 h, at 20 bar N-2). This is the highest yield and selectivity of lactic acid (salt) reported in the literature so far. Reusability experiments showed a partial and gradual loss of activity of the Pt/ZrO2 catalyst, which was attributed to the experimentally observed aggregation of Pt nanoparticles.

Abstract: CsPbI3 is a promising perovskite material for photovoltaic applications in its photoactive perovskite or black phase. However, the material degrades to a photovoltaically inactive or yellow phase at room temperature. Various mitigation strategies are currently being developed to increase the lifetime of the black phase, many of which rely on inducing strains in the material that hinder the black-to-yellow phase transition. Physical insight into how these strategies exactly induce strain as well as knowledge of the spatial extent over which these strains impact the material is crucial to optimize these approaches but is still lacking. Herein, we combine machine learning potential-based molecular dynamics simulations with our in silico strain engineering approach to accurately quantify strained large-scale atomic structures on a nanosecond time scale. To this end, we first model the strain fields introduced by atomic substitutions as they form the most elementary strain sources. We demonstrate that the magnitude of the induced strain fields decays exponentially with the distance from the strain source, following a decay rate that is largely independent of the specific substitution. Second, we show that the total strain field induced by multiple strain sources can be predicted to an excellent approximation by summing the strain fields of each individual source. Finally, through a case study, we illustrate how this additive character allows us to explain how complex strain fields, induced by spatially extended strain sources, can be predicted by adequately combining the strain fields caused by local strain sources. Hence, the strain additivity proposed here can be adopted to further our insight into the complex strain behavior in perovskites and to design strain from the atomic level onward to enhance their sought-after phase stability.