An atomic resolution image of an intercalated structure at a graphene/SiC interface along the growth direction which is determined as a buckled GaN monolayer at the immediate interface with an underlying SiC substrate and ultrathin Ga₂O₃ on top.

Fluorescent carbon quantum dots (CDs) are synthesized and employed as fluorescent nanochemosensors for selective detection of amino acids. A detailed investigation of excitation–emission maps revealed that the fluorescence properties of CDs are intensely and strongly influenced by the interaction at the surface with different amino acids. The discrimination capability was demonstrated by tensor rank decomposition of the differences induced by the surface reaction in the excitation–emission maps and by means of a common machine learning approach based on artificial neural networks.

Here we report the design and fabrication of an array-based sensor, containing functionalized Carbon Dots, Bodipy's and Naphthalimide probes, that shows high fluorescence emissions and sensitivity in the presence of low amounts of TNT explosive. In particular, we have fabricated the first sensor device based on an optical array for the detection of TNT in real samples by using a smartphone as detector. The possibility to use a common smartphone as detector leads to a prototype that can be also used in a real-life field application. The key benefit lies in the possibility of even a nonspecialist operator in the field to simply collect and send data (photos) to the trained artificial intelligence server for rapid diagnosis but also directly to the bomb disposal unit for expert evaluation. This new array sensor contains seven different fluorescent probes that are able to interact via noncovalent interactions with TNT. The interaction of each probe with TNT has been tested in solution by fluorescence titrations. The solid device has been tested in terms of selectivity and linearity toward TNT concentration. Tests performed with other explosives and other nitrogen-based analytes demonstrate the high selectivity for TNT molecules, thus supporting the reliability of this sensor. In addition, TNT can be detected in the range of 98 ng∼985 μg, with a clear different response of each probe to the different amounts of TNT.

An improvement of water supply and sanitation and better management of water resources, especially in terms of water reuse, is one of the priorities of the European Green Deal. In this context, it is crucial to find new strategies to recycle wastewater efficiently in a low-cost and eco-friendly manner. The immobilization of inorganic nanomaterials on polymeric matrices has been drawing a lot of attention in recent years due to the extraordinary properties characterizing the as-obtained nanocomposites. The hybrid materials, indeed, combine the properties of the polymers, such as flexibility, low cost, mechanical stability, high durability, and ease of availability, with the properties of the inorganic counterpart. In particular, if the inorganic fillers are nanostructured photocatalysts, the materials will be able to utilize the energy delivered by light to catalyze chemical reactions for efficient wastewater treatment. Additionally, with the anchoring of the nanomaterials to the polymers, the dispersion of the nanomaterials in the environment is prevented, thus overcoming one of the main limits that impede the application of nanostructured photocatalysts on a large scale. In this work, we will present nanocomposites made of polymers, i.e., polymethyl methacrylate (PMMA), and photocatalytic semiconductors, i.e., TiO₂ nanoparticles (Evonik). MoS₂ nanoflakes were also added as co-catalysts to improve the photocatalytic performance of the TiO₂. The hybrid materials were prepared using the sonication and solution casting method. The nanocomposites were deeply characterized, and their remarkable photocatalytic abilities were evaluated by the degradation of two common water pollutants: methyl orange and diclofenac. The relevance of the obtained results will be discussed, opening the route for the application of these materials in photocatalysis and especially for novel wastewater remediation.

New fluorescent carbon nanoparticles, obtained using artichoke extract, have been used for the ultrasensitive (sub-nanomolar) and selective detection of dopamine in artificial saliva samples.