Beyond conventional characterization: Defect engineering role for sensitivity and selectivity of room-temperature UV-assisted graphene-based NO₂ sensors.

The term graphene-based gas sensors may be too broad, as there are many physicochemical differences within the graphene-based materials (GBM) used for chemiresistive gas sensors. These differences condition the sensitivity, selectivity, recovery, and ultimately the sensing performance of these devices towards air pollutants. Continuous ultraviolet irradiation aids in the desorption of gas molecules and enhances sensor performance.

Generation of Defective Few-Layered Graphene Mesostructures by High-Energy Ball Milling and Their Combination with FeSiCuNbB Microwires for Reinforcing Microwave Absorbing Properties.

Defective few-layered graphene mesostructures (DFLGMs) are produced from graphite flakes by high-energy milling processes. We obtain an accurate control of the generated mesostructures, as well as of the amount and classification of the structural defects formed, providing a functional material for microwave absorption purposes. Working under far-field conditions, competitive values of minimum reflection loss coefficient (RL) = -21.

Real-Time Monitoring of Breath Biomarkers with A Magnetoelastic Contactless Gas Sensor: A Proof of Concept.

In the quest for effective gas sensors for breath analysis, magnetoelastic resonance-based gas sensors (MEGSs) are remarkable candidates. Thanks to their intrinsic contactless operation, they can be used as non-invasive and portable devices. However, traditional monitoring techniques are bound to slow detection, which hinders their application to fast bio-related reactions.

Eco-Friendly Disposable WS Paper Sensor for Sub-ppm NO Detection at Room Temperature.

We developed inexpensive and disposable gas sensors with a low environmental footprint. This approach is based on a biodegradable substrate, paper, and features safe and nontoxic electronic materials. We show that abrasion-induced deposited WS nanoplatelets on paper can be employed as a successful sensing layer to develop high-sensitivity and selective sensors, which operate even at room temperature.

Carbon SH-SAW-Based Electronic Nose to Discriminate and Classify Sub-ppm NO.

In this research, a compact electronic nose (e-nose) based on a shear horizontal surface acoustic wave (SH-SAW) sensor array is proposed for the NO detection, classification and discrimination among some of the most relevant surrounding toxic chemicals, such as carbon monoxide (CO), ammonia (NH), benzene (CH) and acetone (CHO). Carbon-based nanostructured materials (CBNm), such as mesoporous carbon (MC), reduced graphene oxide (rGO), graphene oxide (GO) and polydopamine/reduced graphene oxide (PDA/rGO) are deposited as a sensitive layer with controlled spray and Langmuir-Blodgett techniques. We show the potential of the mass loading and elastic effects of the CBNm to enhance the detection, the classification and the discrimination of NO among different gases by using Machine Learning (ML) techniques (e.