Fornasiero and colleagues describe an alternative strategy for producing hydrogen peroxide through a more sustainable method than the current synthetic approaches. The strategy relies on the use of electrocatalysis, made possible by the use of a catalyst with high efficiency and selectivity toward H 2 O 2 formation. The prepared material is particularly appealing because it does not contain any metal, implying a greener and cheaper synthetic scheme.

This work explains why and how heterochiral and homochiral tripeptides differ in their assembly in water. A characteristic spectroscopic signature is assigned to molecular conformation. We monitor the process as a continuum from the molecular scale to the macroscopic biomaterials so that the final properties are linked to chemical structure of the building blocks. This work lays the foundation for the design of supramolecular hydrogel biomaterials based on short sequences of hydrophobic D-and L-amino acids.

Solution-processed semiconducting transition metal dichalcogenides (TMDs) are at the centre of an ever-increasing research effort in printed (opto)electronics. However, device performance is limited by structural defects resulting from the exfoliation process and poor inter-flake electronic connectivity.Here, we report a new molecular strategy to boost the electrical performance of TMD-based devices via the use of dithiolated conjugated molecules, to simultaneously heal sulfur vacancies in solutionprocessed transition metal disulfides (MS2) and covalently bridge adjacent flakes, thereby promoting percolation pathways for the charge transport. We achieve a reproducible increase by one order-ofmagnitude in field-effect mobility (µFE), current ratios (ION / IOFF), and switching times (τS) of liquid-gated transistors, reaching 10 -2 cm 2 V -1 s -1 , 10 4 , and 18 ms, respectively. Our functionalization strategy is an universal route to simultaneously enhance the electronic connectivity in MS2 networks and tailor on demand their physicochemical properties according to the envisioned applications.

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Short peptide hydrogels are attractive biomaterials but typically suffer from limited mechanical properties. Inclusion of other nanomaterials can serve the dual purpose of hydrogel reinforcement and of conferring additional physicochemical properties ( e. g., self-healing, conductivity), as long as they do not hamper peptide self-assembly. In particular, nanocarbons are ideal candidates, and their physicochemical properties have demonstrated great potential in nanocarbon-polymer gel biomaterials for tissue engineering or drug delivery. Recently, increasing interest in supramolecular hydrogels drove research also on their enhancement with nanocarbons. However, little is known on the effect of nanocarbon morphology on the self-assembly of short peptides, which are among the most popular hydrogel building blocks. In this work, three different oxidized nanocarbons ( i. e., carbon nanotube or CNT as 1D material, graphene oxide sheet or GO as 2D material, and carbon nanohorn or CNH as 3D material) were evaluated for their effects on the self-assembly of the unprotected tripeptide Leu-Phe-Phe at physiological conditions. Supramolecular hydrogels were obtained in all cases, and viscoelastic properties were clearly affected by the nanocarbons, which increased stiffness and resistance to applied stress. Notably, self-healing behavior was observed only in the case of CNTs. Tripeptide-nanotube interaction was noted already in solution prior to self-assembly, with the tripeptide acting as a dispersing agent in phosphate buffer. Experimental and in silico investigation of the interaction between peptide and CNTs suggests that the latter acts as nucleation templates for self-assembly and reassembly. Overall, we provide useful insights for the future design of composite biomaterials with acquired properties.

We present an ultrafast neural network (NN) model, QLKNN, which predicts core tokamak transport heat and particle fluxes. QLKNN is a surrogate model based on a database of 300 million flux calculations of the quasilinear gyrokinetic transport model QuaLiKiz. The database covers a wide range of realistic tokamak core parameters. Physical features such as the existence of a critical gradient for the onset of turbulent transport were integrated into the neural network training methodology. We have coupled QLKNN to the tokamak modelling framework JINTRAC and rapid control-oriented tokamak transport solver RAPTOR. The coupled frameworks are demonstrated and validated through application to three JET shots covering a representative spread of H-mode operating space, predicting turbulent transport of energy and particles in the plasma core. JINTRAC-QLKNN and RAPTOR-QLKNN are able to accurately reproduce JINTRAC-QuaLiKiz T i,e and n e profiles, but 3 to 5 orders of magnitude faster. Simulations which take hours are reduced down to only a few tens of seconds. The discrepancy in the final source-driven predicted profiles between QLKNN and QuaLiKiz is on the order 1%-15%. Also the dynamic behaviour was well captured by QLKNN, with differences of only 4%-10% compared to JINTRAC-QuaLiKiz observed at mid-radius, for a study of density buildup following the L-H transition. Deployment of neural network surrogate models in multi-physics integrated tokamak modelling is a promising route towards enabling accurate and fast tokamak scenario optimization, Uncertainty Quantification, and control applications.

Diphenylalanine is an amyloidogenic building block that can form a versatile array of supramolecular materials. Its shortcomings, however, include the uncontrolled hierarchical assembly into microtubes of heterogeneous size distribution and well-known cytotoxicity. This study rationalized heterochirality as a successful strategy to address both of these pitfalls and it provided an unprotected heterochiral dipeptide that self-organized into a homogeneous and optically clear hydrogel with excellent ability to sustain fibroblast cell proliferation and viability. Substitution of one l -amino acid with its d -enantiomer preserved the ability of the dipeptide to self-organize into nanotubes, as shown by single-crystal XRD analysis, whereby the pattern of electrostatic and hydrogen bonding interactions of the backbone was unaltered. The effect of heterochirality was manifested in subtle changes in the positioning of the aromatic side chains, which resulted in weaker intermolecular interactions between nanotubes. As a result, d -Phe- l -Phe self-organized into homogeneous nanofibrils with a diameter of 4 nm, corresponding to two layers of peptides around a water channel, and yielded a transparent hydrogel. In contrast with homochiral Phe-Phe stereoisomer, it formed stable hydrogels thermoreversibly. d -Phe- l -Phe displayed no amyloid toxicity in cell cultures with fibroblast cells proliferating in high numbers and viability on this biomaterial, marking it as a preferred substrate over tissue-culture plastic. Halogenation also enabled the tailoring of d -Phe- l -Phe self-organization. Fluorination allowed analogous supramolecular packing as confirmed by XRD, thus nanotube formation, and gave intermediate levels of bundling. In contrast, iodination was the most effective strategy to augment the stability of the resulting hydrogel, although at the expense of optical transparency and biocompatibility. Interestingly, iodine presence hindered the supramolecular packing into nanotubes, resulting instead into amphipathic layers of stacked peptides without the occurrence of halogen bonding. By unravelling fine details to control these materials at the meso- and macro-scale, this study significantly advanced our understanding of these systems.

A power-balance model, with radiation losses from impurities and neutrals, gives a unified description of the density limit (DL) of the stellarator, the L-mode tokamak, and the reversed field pinch (RFP). The model predicts a Sudo-like scaling for the stellarator, a Greenwald-like scaling, , for the RFP and the ohmic tokamak, a mixed scaling, , for the additionally heated L-mode tokamak. In a previous paper (Zanca et al 2017 Nucl. Fusion 57 056010) the model was compared with ohmic tokamak, RFP and stellarator experiments. Here, we address the issue of the DL dependence on heating power in the L-mode tokamak. Experimental data from high-density disrupted L-mode discharges performed at JET, as well as in other machines, are taken as a term of comparison. The model fits the observed maximum densities better than the pure Greenwald limit.