Abstract: The investigation of thermal transport properties of novel two-dimensional materials is crucially important in order to assess their potential to be used in future technological applications, such as thermoelectric power generation. In this respect, the lattice thermal transport properties of the monolayer structures of group VA elements (P, As, Sb, Bi, PAs, PSb, PBi, AsSb, AsBi, SbBi, P3As1, P3Sb1, P1As3, and As3Sb1) with a black phosphorus like puckered structure were systematically investigated by first-principles calculations and an iterative solution of the phonon Boltzmann transport equation. Phosphorene was found to have the highest lattice thermal conductivity, , due to its low average atomic mass and strong interatomic bonding character. As a matter of course, anisotropic was obtained for all the considered materials, owing to anisotropy in frequency values and phonon group velocities calculated for these structures. However, the determined linear correlation between the anisotropy in the values of P, As, and Sb is significant. The results corresponding to the studied compound structures clearly point out that thermal (electronic) conductivity of pristine monolayers might be suppressed (improved) by alloying them with the same group elements. For instance, the room temperature of PBi along the armchair direction was predicted to be as low as 1.5 W m(-1) K-1, whereas that of P was predicted to be 21 W m(-1) K-1. In spite of the apparent differences in structural and vibrational properties, we peculiarly revealed an intriguing correlation between the values of all the considered materials as = c(1) + c(2)/m(2), in particular along the zigzag direction. Furthermore, our calculations on compound structures clearly showed that the thermoelectric potential of these materials can be improved by suppressing their thermal properties. The presence of ultra-low values and high electrical conductivity (especially along the armchair direction) makes this class of monolayers promising candidates for thermoelectric applications.

Abstract: Two-dimensional materials (2DMs) continue to attract a lot of attention, particularly for their extreme flexibility and superior thermal properties. Molecular dynamics simulations are among the most powerful methods for computing these properties, but their reliability depends on the accuracy of interatomic interactions. While first principles approaches provide the most accurate description of interatomic forces, they are computationally expensive. In contrast, classical force fields are computationally efficient, but have limited accuracy in interatomic force description. Machine learning interatomic potentials, such as Gaussian Approximation Potentials, trained on density functional theory (DFT) calculations offer a compromise by providing both accurate estimation and computational efficiency. In this work, we present a systematic procedure to develop Gaussian approximation potentials for selected 2DMs, graphene, buckled silicene, and h-XN (X = B, Al, and Ga, as binary compounds) structures. We validate our approach through calculations that require various levels of accuracy in interatomic interactions. The calculated phonon dispersion curves and lattice thermal conductivity, obtained through harmonic and anharmonic force constants (including fourth order) are in excellent agreement with DFT results. HIPHIVE calculations, in which the generated GAP potentials were used to compute higher-order force constants instead of DFT, demonstrated the first-principles level accuracy of the potentials for interatomic force description. Molecular dynamics simulations based on phonon density of states calculations, which agree closely with DFT-based calculations, also show the success of the generated potentials in high-temperature simulations.

Abstract: The installation of urban green infrastructure, particularly green walls, has proven to be an effective strategy for the mitigation of particulate matter (PM) pollution and the urban heat island effect. For the interaction between vegetation, PM and the local microclimate, wind flow is the main driving force. In order to investigate these interactions in detail, it is important to know how air flows through vegetation. This study proposes a method based on the DarcyForchheimer equation, where vegetation is considered as a porous medium and several plant species and the effects of plant morphological characteristics are examined both experimentally and using computer simulations. Results showed that the DarcyForchheimer model is a simple and robust way to describe air flow through vegetation regardless of its morphology. This research provides a new vision on studying aerodynamic properties of vegetation in relation to their morphology and provides opportunities for model the interaction between vegetation and its environment.

Abstract: Cities with resilience to climate change appear to be a vision of the future, but are inevitable to ensure the quality of life for citizens and to avoid an increase in civilian mortality. Urban green infrastructure (UGI), with the focus on vertical green, poses a beneficial mitigation and adaptation strategy for challenges such as climate change through cooling effects on building and street level. This review article explores recent literature regarding this considerable topic and investigates how green walls can be applied to mitigate this problem. Summary tables (see additional information) and figures are presented that can be used by policy makers and researchers to make informed decisions when installing green walls in built-up environments. At last, knowledge gaps are uncovered that need further investigation to exploit the benefits at its best.

Abstract: Since many materials behave as heterogeneous intimate mixtures with which each photon interacts differently, the relationship between spectral reflectance and material composition is very complex. Quantitative validation of spectral unmixing algorithms requires high-quality ground truth fractional abundance data, which are very difficult to obtain.In this work, we generated a comprehensive hyperspectral dataset of intimate mineral powder mixtures by homogeneously mixing five different clay powders (Kaolin, Roof clay, Red clay, mixed clay, and Calcium hydroxide). In total 325 samples were prepared. Among the 325 samples, 60 mixtures were binary, 150 were ternary, 100 were quaternary, and 15 were quinary. For each mixture (and pure clay powder), reflectance spectra are acquired by 13 different sensors, with a broad wavelength range between the visible and the long-wavelength infrared regions (i.e., between 350 nm and 15385 nm) and with a large variation in sensor types, platforms, and acquisition conditions. We will make this dataset public, to be used by the community for the validation of nonlinear unmixing methodologies (https://github.com/VisionlabUA/Multisensor_datasets)

Abstract: CO2 dissociation and its subsequent conversion into added-value chemicals is a promising strategy for recycling CO2 gas into reusable products. One of the possible methods is direct plasma-induced dissociation. In this work we study the efficiency of CO2 dissociation in pulsed atmospheric-pressure gas discharge between two conducting electrodes by a 0-D numerical plasma model. The purpose of the study is to provide results on the optimal conditions of CO2 conversion with respect to the energy efficiency and dissociation by varying the maximum power density value and the pulse length. The power density is directly related to the discharge current and the reduced electric field in the discharge. We consider pulse lengths in the range from hundreds of nanosecond up to milliseconds. The results obtained show that the dissociation degree and energy efficiency are sensitive to the pulse length (duration) and the power density, so that a considerable improvement of the discharge performance can be achieved by fine-tuning these parameters. The study is intended to provide guidance in designing an experimental set-up and a power supply with the characteristics necessary to achieve optimal conversion.

Abstract: Indoor and outdoor concentrations of atmospheric gaseous pollutants as well as composition, size, and morphology of particulate matter have been investigated at the monastery of San Jerónimo in Granada (Southern Spain). Complementary micro- and nano-analytical techniques were applied; elemental and mineralogical composition and morphological characteristics of particulate matter were investigated combining electron probe microanalysis at the single particle level, and bulk aerosol samples were analyzed using energy-dispersive X-ray fluorescence, X-ray diffraction, scanning electron microscopy with energy-dispersive X-ray analyzer and transmission electron microscopy (TEM). Microclimatic conditions at the monastery were monitored, and gas concentrations were assessed by means of diffusion tubes subsequently analyzed with ion chromatography. Results revealed high abundances of soil dust particles (aluminosilicates, calcite, dolomite, quartz), salt aerosols (chlorides, sulfates and ammonium-rich salts), and NO2 and SO2 both outdoors and indoors. Amorphous black carbon particles had surprisingly high abundances for Granada, a non-industrialized city. The composition of indoor particles corresponds to severe weathering affecting the construction materials and artworks inside the church; moreover their composition promotes a feedback process that intensifies the deterioration. Chemical reactions between chloride-rich salts and pigments from paintings were confirmed by TEM analyses. Indoors, blackening of surface decorative materials is fostered by particle re-suspension due to cleaning habits in the monastery (i.e. dusting). This is the first air quality study performed in a monument in the city of Granada with the aim of developing a strategy for preventive conservation.