Abstract: Nanoparticle assemblies can be investigated in 3 dimensions using electron tomography. However, it is not straightforward to obtain quantitative information such as the number of particles or their relative position. This becomes particularly difficult when the number of particles increases. We propose a novel approach in which prior information on the shape of the individual particles is exploited. It improves the quality of the reconstruction of these complex assemblies significantly. Moreover, this quantitative Sparse Sphere Reconstruction approach yields directly the number of particles and their position as an output of the reconstruction technique, enabling a detailed 3D analysis of assemblies with as many as 10 000 particles. The approach can also be used to reconstruct objects based on a very limited number of projections, which opens up possibilities to investigate beam sensitive assemblies where previous reconstructions with the available electron tomography techniques failed.

Abstract: Silver nanoparticles are widely used in the field of plasmonics because of their unique optical properties. The wavelength-dependent surface plasmon resonance gives rise to a strongly enhanced electromagnetic field, especially at so-called hot spots located in the nanogap in-between metal nanoparticle assemblies. Therefore, the interparticle distance is a decisive factor in plasmonic applications, such as surface-enhanced Raman spectroscopy (SERS). In this study, the aim is to engineer this interparticle distance for silver nanospheres using a convenient wet-chemical approach and to predict and quantify the corresponding enhancement factor using both theoretical and experimental tools. This was done by building a tunable ultrathin polymer shell around the nanoparticles using the layer-by-layer method, in which the polymer shell acts as the separating interparticle spacer layer. Comparison of different theoretical approaches and corroborating the results with SERS analytical experiments using silver and silver−polymer core−shell nanoparticle clusters as SERS substrates was also done. Herewith, an approach is provided to estimate the extent of plasmonic near-field enhancement both theoretically as well as experimentally.

Abstract: A Ti-Beta zeolite was used in gas phase photocatalytic CO2 reduction to reduce the charge recombination rate and increase the surface area compared to P25 as commercial benchmark, reaching 607 m2 g-1. By adding Pt nanoparticles, the selectivity can be tuned toward CO, reaching a value of 92% and a turnover frequency (TOF) of 96 µmol.gcat-1.h-1, nearly an order of magnitude higher in comparison with P25. By adding Pd nanoparticles the selectivity can be shifted from CO (70% for a bare Ti-Beta zeolite), toward CH4 as the prevalent species (60%). In this way, the selectivity toward CO or CH4 can be tuned by either using Pt or Pd. The TOF values obtained in this work outperform reported state-of-the-art values in similar research. The improved activity by adding the nanoparticles was attributed to an improved charge separation efficiency, together with a plasmonic contribution of the metal nanoparticles under the applied experimental conditions.

Abstract: Immune checkpoint blockade involves targeting immune
regulatory molecules with antibodies. Preclinically, complex multiantibody
regimes of both inhibitory and stimulatory targets are a promising
candidate for the next generation of immunotherapy. However, in this
setting, the antibody platform may be limited due to excessive toxicity
caused by off target effects as a result of systemic administration. RNA
can be used as an alternate to antibodies as it can both downregulate
immunosuppressive checkpoints (siRNA) or induce expression of
immunostimulatory checkpoints (mRNA). In this study, we demonstrate
that the combination of both siRNA and mRNA in a single
formulation can simultaneously knockdown and induce expression of
immune checkpoint targets, thereby reprogramming the tumor
microenvironment from immunosuppressive to immunostimulatory
phenotype. To achieve this, RNA constructs were synthesized and
formulated into stable nucleic acid lipid nanoparticles (SNALPs); the SNALPs produced were 140−150 nm in size with >80%
loading efficiency. SNALPs could transfect macrophages and B16F10 cells in vitro resulting in 75% knockdown of inhibitory
checkpoint (PDL1) expression and simultaneously express high levels of stimulatory checkpoint (OX40L) with minimal
toxicity. Intratumoral treatment with the proposed formulation resulted in statistically reduced tumor growth, a greater
density of CD4+ and CD8+ infiltrates in the tumor, and immune activation within tumor-draining lymph nodes. These data
suggest that a single RNA-based formulation can successfully reprogram multiple immune checkpoint interactions on a
cellular level. Such a candidate may be able to replace future immune checkpoint therapeutic regimes composed of both
stimulatory- and inhibitory-receptor-targeting antibodies.

Abstract: Even at low temperatures, metal nanoparticles (NPs) possess atomic dynamics that are key for their properties but challenging to elucidate. Recent experimental advances allow obtaining atomic‐resolution snapshots of the NPs in realistic regimes, but data acquisition limitations hinder the experimental reconstruction of the atomic dynamics present within them. Molecular simulations have the advantage that these allow directly tracking the motion of atoms over time. However, these typically start from ideal/perfect NP structures and, suffering from sampling limits, provide results that are often dependent on the initial/putative structure and remain purely indicative. Here, by combining state‐of‐the‐art experimental and computational approaches, how it is possible to tackle the limitations of both approaches and resolve the atomistic dynamics present in metal NPs in realistic conditions is demonstrated. Annular dark‐field scanning transmission electron microscopy enables the acquisition of ten high‐resolution images of an Au NP at intervals of 0.6 s. These are used to reconstruct atomistic 3D models of the real NP used to run ten independent molecular dynamics simulations. Machine learning analyses of the simulation trajectories allows resolving the real‐time atomic dynamics present within the NP. This provides a robust combined experimental/computational approach to characterize the structural dynamics of metal NPs in realistic 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.