Search

Improper development of land uses in the city leads to climate changes, resulting in an increase in GW and the formation of UHIs. These changes have adverse effects on people’s level of comfort. This research is supposed to extract the optimal model by proving the relationship between the physical arrangement of the architecture of high-rise buildings in residential complexes and reducing the adverse effects of this. Therefore, in this research, four models of solitary, environmental, combined, and rowly block arrangement were investigated based on numerical calculation methods and CFD simulation. These simulations were done by ENVI-meto software based on air temperature, relative humidity, wind speed, and thermal comfort in the open space. The results showed that the type of physical arrangement of buildings can increase air temperature for GW by up to 3 °C and UHIs by 0.5 °C. The combined pattern is the most optimal in this section due to its more compact structure than the solitary pattern. Regarding the effect of relative humidity on climate changes, the solitary pattern has the lowest percentage of relative humidity compared to other patterns due to more air circulation in its physical structure. Also, the type of physical arrangement of buildings can improve the wind speed for GW by up to 0.2 m/s and for UHIs by up to 0.7 m/s. Based on this, the most optimal model is the environmental pattern, because the physical structures of the buildings are an obstacle in wind circulation. The fluctuation range of the PMV index for the intensity of GW effects on thermal comfort, is 0.7°, and the fluctuation range of this index for the power of UHIs is about 0.2°. The solitary pattern is the most optimal pattern to reduce the severity of adverse effects of GW and UHIs; this is due to the scattered distribution of blocks in this pattern. In general, according to the research findings, it can be concluded that the most optimal pattern to reduce the severity of the adverse effects of GW is solitary and environmental patterns, and to reduce the severity of the negative impact of UHIs, the solitary pattern is used. [ABSTRACT FROM AUTHOR]

Improper development of land uses in the city leads to climate changes, resulting in an increase in GW and the formation of UHIs. These changes have adverse effects on people's level of comfort. This research is supposed to extract the optimal model by proving the relationship between the physical arrangement of the architecture of high-rise buildings in residential complexes and reducing the adverse effects of this. Therefore, in this research, four models of solitary, environmental, combined, and rowly block arrangement were investigated based on numerical calculation methods and CFD simulation. These simulations were done by ENVI-meto software based on air temperature, relative humidity, wind speed, and thermal comfort in the open space. The results showed that the type of physical arrangement of buildings can increase air temperature for GW by up to 3 °C and UHIs by 0.5 °C. The combined pattern is the most optimal in this section due to its more compact structure than the solitary pattern. Regarding the effect of relative humidity on climate changes, the solitary pattern has the lowest percentage of relative humidity compared to other patterns due to more air circulation in its physical structure. Also, the type of physical arrangement of buildings can improve the wind speed for GW by up to 0.2 m/s and for UHIs by up to 0.7 m/s. Based on this, the most optimal model is the environmental pattern, because the physical structures of the buildings are an obstacle in wind circulation. The fluctuation range of the PMV index for the intensity of GW effects on thermal comfort, is 0.7°, and the fluctuation range of this index for the power of UHIs is about 0.2°. The solitary pattern is the most optimal pattern to reduce the severity of adverse effects of GW and UHIs; this is due to the scattered distribution of blocks in this pattern. In general, according to the research findings, it can be concluded that the most optimal pattern to reduce the severity of the adverse effects of GW is solitary and environmental patterns, and to reduce the severity of the negative impact of UHIs, the solitary pattern is used.

Abstract Ultra‐wide bandgap (UWBG) materials such as AlN and BN hold great promise for future power electronics due to their exceptional properties. They exhibit large bandgaps, high breakdown fields, high thermal conductivity, and high mechanical strengths. AlN and BN have been extensively researched, however, their alloys, BxAl1−xN, are much less studied despite their ability to offer tunable properties by adjusting x. In this article, the electronic properties of 17 recently predicted ground states of BxAl1−xN in the x = 0 − 1 range are predicted using first‐principles density functional theory and many‐body perturbation theory within GW approximation. All the BxAl1−xN structures are found to be UWBG materials and have bandgaps that vary linearly from that of wurtzite‐phase (w) AlN (6.19 eV) to that of w‐BN (7.47 eV). The bandstructures of BxAl1−xN show that a direct‐to‐indirect bandgap crossover occurs near x = 0.25. Furthermore, it is found that BxAl1−xN alloys have much larger dielectric constants than the constituent bulk materials (AlN = 9.3 ɛ0 or BN = 7.3 ɛ0), with values reaching as high as 12.1 ɛ0. These alloys are found to exhibit large dielectric breakdown fields in the range 9–35 MV cm−1 with a linear dependence on x. This work provides the much needed advancement in the understanding of the properties of BxAl1−xN to aid their application in next‐generation devices.

In the pursuit of advancing solar energy technologies, this study presents 20 direct and quasi-direct band gap silicon crystalline semiconductors that satisfy the Shockley-Queisser limit, a benchmark for solar cell efficiency. Employing two evolutionary algorithm-based searches, we optimize structures and calculate fitness function using the DFTB method and Gaussian approximation potential. Following the preselection of structures based on energy considerations, we further optimize them using PBEsol DFT. Subsequently, we screen the structures based on their band gap, employing a DFTB method tailored for band gap calculation of silicon crystals. To ensure accurate band gap determination, we employ HSE and GW methods. To validate the structural stability, we employ phonon analysis via linear regression algorithm applied to PBEsol DFT data. Significantly, the structures unveiled in this study are of great importance due to their proven stability from both mechanical and dynamic perspectives. Furthermore, the ductility and low density of certain structures enhance their potential application. We examine the optical properties by studying the imaginary part of the dielectric function by solving the Bethe–Salpeter Equation on top of GW approximation. By calculating the SLME, we achieve an efficiency of 32.7% for Si 22 at a thickness of 500 nm. Moreover, the study harnesses various machine learning algorithms to develop a predictive model for the band gap energy of these silicon structures. Input data for machine learning models are derived from structural MBTR and SOAP descriptors, as well as DFT outputs. Notably, the results reveal that features extracted from DFT outperform the MBTR and SOAP descriptors. [Display omitted] • 20 Si-crystal discovered for solar cells with direct/quasi-direct band gaps. • DFTB band structure calculations agreed well with GW and HSE methods. • Stability confirmed dynamically, thermodynamically, and mechanically using DFT. • Optical properties indicate high suitability for solar cell production. • DFT features outperformed MBTR and SOAP in predicting band gaps. [ABSTRACT FROM AUTHOR]