We present a generalized table of extinction coefficient data for silver nanoparticles from 8 to 100 nm. This table allows for easy and quick estimation of the concentration and size of modified and mono-dispersed silver nanoparticles from their optical spectra. We obtained data by determining the silver content of citrate-stabilised silver nanoparticles using sodium cyanide to dissolve the nanoparticles, and measuring solution conductivity with a pH meter and a cyanide-ion selective electrode. The quantification of the silver ion concentration enabled the calculation of extinction coefficients. Experimentally calculated extinction coefficients, in the current work, are in good agreement with collated literature values measured by different authors with non-standardized methodology and each for a limited range of particle size. They are also in good agreement with our theoretical calculations using Mie theory. Thus, we provide a highly standardized and comprehensive tabulated reference data-set.

The monolithic three-dimensional (3D) graphene network is used as the support for Pt nanoparticles (NPs) to fabricate an advanced 3D graphene-based electrocatalyst. Distinct from previous strategies, the monodispersed Pt NPs with ultrafine particle size (∼3 nm) are synthesized using ferritin protein nanocages as the template and subsequently self-assembled on the 3D graphene by leveraging on the hydrophobic interaction between the ferritin and the graphene. Following the self-assembly, the ferritins are removed, resulting in a stable Pt NP/3D graphene composite. The composite exhibits much enhanced electrocatalytic activity for methanol oxidation as compared with both Pt NP/chemically reduced graphene oxide (Pt/r-GO) and state-of-the-art Pt/C catalyst. The observed electrocatalytic activity also shows marked improvement over Pt/3D graphene prepared by pulse electrodeposition of Pt. This study demonstrates that protein nanocage templating and assembly are promising strategies for the fabrication of functional composites in catalysis and fuel cell applications.

The cross-linking approach combined with MS for protein structure determination is one of the most striking examples of multidisciplinary success. Indeed, it has become clear that the bottleneck of the method was the detection and the identification of low-abundance cross-linked peptides in complex mixtures. Sample treatment or chromatography separation partially addresses these issues. However, the main problem comes from over-represented unmodified peptides, which do not yield any structural information. A real breakthrough was provided by high mass accuracy measurement, because of the outstanding technical developments in MS. This improvement greatly simplified the identification of cross-linked peptides, reducing the possible combinations matching with an observed m/z value. In addition, the huge amount of data collected has to be processed with dedicated software whose role is to propose distance constraints or ideally a structural model of the protein. In addition to instrumentation and algorithms efficiency, significant efforts have been made to design new cross-linkers matching all the requirements in terms of reactivity and selectivity but also displaying probes or reactive systems facilitating the isolation, the detection of cross-links, or the interpretation of MS data. These chemical features are reviewed and commented on in the light of the more recent strategies.