Synthetic chiral molecular nanographenes: the key figure of the racemization barrier.

Chirality is one of the most intriguing concepts of chemistry, involving living systems and, more recently, materials science. In particular, the bottom-up synthesis of molecular nanographenes endowed with one or several chiral elements is a current challenge for the chemical community. The wilful introduction of defects in the sp2 honeycomb lattice of molecular nanographenes allows the preparation of chiral molecules with tuned band-gaps and chiroptical properties. There are two requirements that a system must fulfill to be chiral: (i) lack of inversion elements (planes or inversion centres) and (ii) to be configurationally stable. The first condition is inherently established by the symmetry group of the structure, however, the limit between conformational and configurational isomers is not totally clear. In this feature article, the chirality and dynamics of synthetic molecular nanographenes, with special emphasis on their racemization barriers and, therefore, the stability of their chiroptical properties are discussed. The general features of nanographenes and their bottom-up synthesis, including the main defects inducing chirality in molecular nanographenes are firstly discussed. In this regard, the most common topological defects of molecular NGs as well as the main techniques used for determining their energy barriers are presented. Then, the manuscript is structured according to the dynamics of molecular nanographenes, classifying them in four main groups, depending on their respective isomerization barriers, as flexible, detectable, isolable and rigid nanographenes. In these sections, the different strategies used to increase the isomerization barrier of chiral molecular nanographenes that lead to configurationally stable nanographenes with defined chiroptical properties are discussed.

Robotic-Based Well-Being Monitoring and Coaching System for the Elderly in Their Daily Activities.

The increasingly ageing population and the tendency to live alone have led science and engineering researchers to search for health care solutions. In the COVID 19 pandemic, the elderly have been seriously affected in addition to suffering from isolation and its associated and psychological consequences. This paper provides an overview of the RobWell (Robotic-based Well-Being Monitoring and Coaching System for the Elderly in their Daily Activities) system. It is a system focused on the field of artificial intelligence for mood prediction and coaching. This paper presents a general overview of the initially proposed system as well as the preliminary results related to the home automation subsystem, autonomous robot navigation and mood estimation through machine learning prior to the final system integration, which will be discussed in future works. The main goal is to improve their mental well-being during their daily household activities. The system is composed of ambient intelligence with intelligent sensors, actuators and a robotic platform that interacts with the user. A test smart home system was set up in which the sensors, actuators and robotic platform were integrated and tested. For artificial intelligence applied to mood prediction, we used machine learning to classify several physiological signals into different moods. In robotics, it was concluded that the ROS autonomous navigation stack and its autodocking algorithm were not reliable enough for this task, while the robot's autonomy was sufficient. Semantic navigation, artificial intelligence and computer vision alternatives are being sought.

Design and Calibration of a Low-Cost SDI-12 Soil Moisture Sensor.

Water is the main limiting factor in agricultural production as well as a scarce resource that needs to be optimized. The measurement of soil water with sensors is an efficient way for optimal irrigation management. However, commercial sensors are still too expensive for most farmers. This paper presents the design, development and calibration of a new capacitive low-cost soil moisture sensor that incorporates SDI-12 communication, allowing one to select the calibration equation for different soils. The sensor was calibrated in three different soils and its variability and accuracy were evaluated. Lower but cost-compensated accuracy was observed in comparing it with commercial sensors. Field tests have demonstrated the temperature influence on the sensor and its capability to efficiently detect irrigation and rainfall events.