Abstract: Triple-modal imaging magnetic nanocapsules, encapsulating hydrophobic superparamagnetic iron oxide nanoparticles, are formulated and used to magnetically target solid tumours after intravenous administration in tumour-bearing mice. The engineered magnetic polymeric nanocapsules m-NCs are ~200 nm in size with negative Zeta potential and shown to be spherical in shape. The loading efficiency of superparamagnetic iron oxide nanoparticles in the m-NC was ~100%. Up to ~3- and ~2.2-fold increase in tumour uptake at 1 and 24 h was achieved, when a static magnetic field was applied to the tumour for 1 hour. m-NCs, with multiple imaging probes (e.g. indocyanine green, superparamagnetic iron oxide nanoparticles and indium-111), were capable of triple-modal imaging (fluorescence/magnetic resonance/nuclear imaging) in vivo. Using triple-modal imaging is to overcome the intrinsic limitations of single modality imaging and provides complementary information on the spatial distribution of the nanocarrier within the tumour. The significant findings of this study could open up new research perspectives in using novel magnetically-responsive nanomaterials in magnetic-drug targeting combined with multi-modal imaging.

Abstract: Lithium-ion battery cathode materials have relied on cationic redox reactions until the recent discovery of anionic redox activity in Li-rich layered compounds which enables capacities as high as 300 mAh g(-1). In the quest for new high-capacity electrodes with anionic redox, a still unanswered question was remaining regarding the importance of the structural dimensionality. The present manuscript provides an answer. We herein report on a beta-Li2IrO3 phase which, in spite of having the Ir arranged in a tridimensional (3D) framework instead of the typical two-dimensional (2D) layers seen in other Li-rich oxides, can reversibly exchange 2.5 e(-) per Ir, the highest value ever reported for any insertion reaction involving d-metals. We show that such a large activity results from joint reversible cationic (Mn+) and anionic (O-2)(n-) redox processes, the latter being visualized via complementary transmission electron microscopy and neutron diffraction experiments, and confirmed by density functional theory calculations. Moreover, beta-Li2IrO3 presents a good cycling behaviour while showing neither cationic migration nor shearing of atomic layers as seen in 2D-layered Li-rich materials. Remarkably, the anionic redox process occurs jointly with the oxidation of Ir4+ at potentials as low as 3.4 V versus Li+/Li-0, as equivalently observed in the layered alpha-Li2IrO3 polymorph. Theoretical calculations elucidate the electrochemical similarities and differences of the 3D versus 2D polymorphs in terms of structural, electronic and mechanical descriptors. Our findings free the structural dimensionality constraint and broaden the possibilities in designing high-energy-density electrodes for the next generation of Li-ion batteries.

Abstract: Nanomaterials are materials that have at least one dimension in the nanometer length scale, which corresponds to a billionth of a meter. When three dimensions are confined to the nanometer scale, these materials are referred to as nanoparticles. These materials are of great interest since they exhibit unique physical and chemical properties that cannot be observed for bulk systems. Due to their unique and often superior properties, nanomaterials have become central in the field of electronics, catalysis, and medicine. Moreover, they are expected to be one of the most promising systems to tackle many challenges that our society is facing, such as reducing the emission of greenhouse gases and finding effective treatments for cancer. The unique properties of nanomaterials are linked to their size, shape, structure, and composition. If one is able to measure the positions of the atoms, their chemical nature, and the bonding between them, it becomes possible to predict the physicochemical properties of nanomaterials. In this manner, the development of novel nanostructures can be triggered. However, the morphology and structure of nanomaterials are highly sensitive to the conditions for relevant applications, such as elevated temperatures or intense light illumination. Furthermore, any small change in the local structure at higher temperatures or pressures may significantly modify their performance. Hence, three-dimensional (3D) characterization of nanomaterials under application-relevant conditions is important in designing them with desired functional properties for specific applications. Among different structural characterization approaches, transmission electron microscopy (TEM) is one of the most efficient and versatile tools to investigate the structure and composition of nanomaterials since it can provide atomically resolved images, which are sensitive to the local 3D structure of the investigated sample. However, TEM only provides two-dimensional (2D) images of the 3D nanoparticle, which may lead to an incomplete understanding of their structure-property relationship. The most known and powerful technique for the 3D characterization of nanomaterials is electron tomography, where the images of a nanostructured material taken from different directions are mathematically combined to retrieve its 3D structure. Although these experiments are already state-of-the-art, 3D characterization by TEM is typically performed under ultra-high vacuum conditions and at room temperature. Such conditions are unfortunately not sufficient to understand transformations during synthesis or applications of nanomaterials. This limitation can be overcome by in situ TEM where external stimuli, such as heat, gas, and liquids, can be controllably introduced inside the TEM using specialized holders. However, there are some technical limitations to successful perform 3D in situ electron tomography experiments. For example, the long acquisition time required to collect a tilt series limits this technique when one wants to observe 3D dynamic changes with atomic resolution. A solution for this problem is the estimation of the 3D structure of nanomaterials from 2D projection images acquired along a single viewing direction. For this purpose, annular dark field scanning TEM (ADF STEM) imaging mode provides a valuable tool for quantitative structural investigation of nanomaterials from single 2D images due to its thickness and mass sensitivity. For quantitative analysis, an ADF STEM image is considered as a 2D array of pixels where relative variation of pixel intensity values is proportional to the total number of atoms and the atomic number of the elements in the sample. By applying advanced statistical approaches to these images, structural information, such as the number or types of atoms, can be retrieved with high accuracy and precision. The outcome can then be used to build a 3D starting model for energy minimization by atomistic simulations, for example, molecular dynamics simulations or the Monte Carlo method. However, this methodology needs to be further evaluated for in situ experiments. This thesis is devoted to presenting robust approaches to accurately define the 3D atomic structure of nanoparticles under application-relevant conditions and understand the mechanism behind the atomic-scale dynamics in nanoparticles in response to environmental stimuli.

Abstract: Ever since the industrial revolution, the emission of greenhouse gasses dramatically increased, resulting in high CO2 concentration in the atmosphere. The electrochemical conversion of CO2 to value added products, such as carbon monoxide, formic acid, methane, ethylene and ethanol is a very promising strategy to inhibit CO2 emissions. Nevertheless, at the moment, the electrochemical CO2 reduction (eCO2R) is not yet industrially viable, mainly due to the lack of good electrocatalysts. On the other hand, core-shell nanoparticles (NPs) have emerged over the last couple of years as promising candidates. It is believed that bimetallic enhancement effects are behind the improved performance of these core-shell NPs when compared to the individual metals. Although widely investigated, there are still some remaining issues and/or open questions. Indeed, the development of a robust and straightforward synthesis method along with fundamental insight into their resistance towards electrochemical stress remains absent. A good control over morphology, size and composition is key in determining which properties are beneficial for the eCO2R. Since these catalysts are designed to be implemented in electrolyzers, they have to maintain long-term performance. This makes the design of a reproducible method, unveiling structure-performance relationships the effect of electrochemical stress, a crucial aspect. Exploring and modifying existing synthesis methods, have led to the acquisition of a robust and reproducible synthesis method where thermal decomposition of the Cu core is combined with the galvanic replacement of Ag in organic solvents. The implementation of this method has led to the design of a wide variety of Cu-Ag bimetallic NPs and enabled to investigate their composition-selectivity profile. Introducing Ag on Cu suppressed hydrogen and increased the CO formation. CO production was boosted by using Cu@Ag core-shells and was promoted even more by changing the type of electrolyte. As these nanoparticles suffered from degradation, the 3D mapping of the structural changes of Cu@Ag core-shells under operating conditions led to the hypothesis of a two-step degradation mechanism where initially Cu leaching was observed with the subsequent sintering of the Ag shells. One approach to avoid this electrochemical degradation, investigated in this research, was the application of an ultrathin carbon layer to protect the active layer. This ultrathin carbon layer operated as a protective layer, suppressing hydrogen production and increasing the stability of the electrocatalyst. In conclusion, the product selectivity can be tuned by using different Cu-Ag bimetallic nanoparticles synthesized through a robust method. Their unique degradation pathway of Cu@Ag core-shell nanoparticles has led to the proposition of a more accurate stabilization strategy. These findings can contribute significantly in the quest for improved electrocatalysts for the eCO2R.