In this work we describe a novel method for highly efficient functionalization of single wall carbon nanotubes (SWCNTs) by DNA wrapping. Exposure of SWCNTs to gamma-irradiation (50 kGy) has lowered by one order of magnitude the amount of single stranded deoxyribonucleic acid (ssDNA) required for SWCNT modification. The resulting hybrids of gamma-irradiated SWCNTs and ssDNA were characterized by optical absorbance spectroscopy, Raman spectroscopy and Fourier transform infrared spectroscopy. Atomic force microscopy was used to investigate the morphology of hybrids. While gamma-irradiation in three different media has significantly improved the process of SWCNT dispersion, irradiation in ammonia was the most efficient. The gamma-irradiated SWCNTs functionalized with ssDNA were stabilized by electrostatic forces. This preliminary study suggests that gamma-irradiation can significantly improve the functionalization of SWCNTs with DNA.

The present study investigated the hemolytic properties of fullerene (C(60)) nanoparticles prepared by solvent exchange using tetrahydrofuran (nC(60)THF), or by mechanochemically assisted complexation with macrocyclic oligosaccharide gamma-cyclodextrin (nC(60)CDX) or the copolymer ethylene vinyl acetate-ethylene vinyl versatate (nC(60)EVA-EVV). The spectrophotometrical analysis of hemoglobin release revealed that only nC(60)THF, but not nC(60)CDX or nC(60)EVA-EVV, was able to cause lysis of human erythrocytes in a dose- and time-dependent manner. Atomic force microscopy revealed that nC(60)THF-mediated hemolysis was preceded by erythrocyte shrinkage and increase in cell surface roughness. A flow cytometric analysis confirmed a decrease in erythrocyte size and demonstrated a significant increase in reactive oxygen species production in red blood cells exposed to nC(60)THF. The nC(60)THF-triggered hemolytic activity was efficiently reduced by the antioxidants N-acetylcysteine and butylated hydroxyanisole, as well as by serum albumin, the most abundant protein in human blood plasma. These data indicate that nC(60)THF can cause serum albumin-preventable hemolysis through oxidative stress-mediated damage of the erythrocyte membrane.

Scalable and effective calibration is a fundamental requirement for low-cost air quality (AQ) monitoring systems and will enable accurate and pervasive monitoring in cities. Suffering from environmental interferences and fabrication variance, these devices need to encompass sensor-specific and complex calibration processes for reaching a sufficient accuracy to be deployed as indicative measurement devices in AQ monitoring networks. Concept and sensor drift often force the calibration process to be frequently repeated. These issues lead to unbearable calibration costs, which denies their massive deployment when accuracy is a concern. In this work, we propose a zero transfer samples, global calibration methodology as a technological enabler for Internet of Things (IoT) AQ multisensory devices, which relies on low-cost particulate matter (PM) sensors. This methodology is based on field recorded responses from a limited number of IoT AQ multisensors units and machine learning (ML) concepts and can be universally applied to all units of the same type. A multiseason test campaign has shown that, when applied to different sensors, this methodology’s performances match those of state-of-the-art methodology, which requires to derive different calibration parameters for each different unit. If confirmed, these results show that, when properly derived, a global calibration law can be exploited for a large number of networked devices with dramatic cost reduction eventually allowing massive deployment of accurate IoT AQ monitoring devices. Furthermore, this calibration model could be easily embedded onboard of the device or implemented on the edge allowing immediate access to accurate readings for personal exposure monitor applications as well as reducing long-range data transfer needs.