Application of machine learning in perovskite materials and devices:A review

Metal-halide hybrid perovskite materials are excellent candidates for solar cells and photoelectric devices.In recent years,machine learning(ML)techniques have developed rapidly in many fields and provided ideas for material discovery and design.ML can be applied to discover new materials quickly and effectively,with significant savings in resources and time compared with traditional experiments and density functional theory(DFT)calculations.In this review,we present the application of ML in per-ovskites and briefly review the recent works in the field of ML-assisted perovskite design.Firstly,the advantages of perovskites in solar cells and the merits of ML applied to perovskites are discussed.Secondly,the workflow of ML in perovskite design and some basic ML algorithms are introduced.Thirdly,the applications of ML in predicting various properties of perovskite materials and devices are reviewed.Finally,we propose some prospects for the future development of this field.The rapid devel-opment of ML technology will largely promote the process of materials science,and ML will become an increasingly popular method for predicting the target properties of materials and devices.

Design and construction of high and large span cast-in-place reinforced concrete cantilever flowering frame beam

The high and large span cast-in-place reinforced concrete cantilever structure of the office building of some court, which is located I-steel at the cantilever and used steel pipe scaffold as the support, has guaranteed the frame body and structure security by the frame body calculating, on-site test and reasonable construction order.

Bilateral U-Net semantic segmentation with spatial attention mechanism

Aiming at the problem that the existing models have a poor segmentation effect on imbalanced data sets with small-scale samples,a bilateral U-Net network model with a spatial attention mechanism is designed.The model uses the lightweight MobileNetV2 as the backbone network for feature hierarchical extraction and proposes an Attentive Pyramid Spatial Attention(APSA)module compared to the Attenuated Spatial Pyramid module,which can increase the receptive field and enhance the information,and finally adds the context fusion prediction branch that fuses high-semantic and low-semantic prediction results,and the model effectively improves the segmentation accuracy of small data sets.The experimental results on the CamVid data set show that compared with some existing semantic segmentation networks,the algorithm has a better segmentation effect and segmentation accuracy,and its mIOU reaches 75.85%.Moreover,to verify the generality of the model and the effectiveness of the APSA module,experiments were conducted on the VOC 2012 data set,and the APSA module improved mIOU by about 12.2%.

Major Issues of Post-earthquake Housing Construction during Resettlement

Natural disasters provide an acute image of how man-made technologies are a cause of conflict when it comes to nature. It is man versus wild in its true means. The nature lets us grow and increase our settlements. We encroach on other animals＇ territories and it is only when the environment＇s patience runs out that it retaliates in forms of natural disasters. These disasters affect numerous lives and kill a lot ofhnmans. This is the main reason why we require more stable structures and preventive measures to battle the wrath of the nature. Rescue and search operations are conducted by many different government and private agencies including NGOs. These operations aim at providing the required relief and supplies after the disaster. Injured people need to be treated. People in dangerous zones need to be evacuated. Help is needed in many forms. Out of the many natural disasters, this paper will focus on the occurrence of earthquakes. Severe earthquakes destroy buildings and structures like roads, bridges etc. and wreak havoc in the community. Earthquakes largely damage all human constructions, including houses. This is the reason why a reconstruction program for dwellings and housings is of utmost importance. A home is only secondary to basic needs such as food and water. A well-planned strategy is important when it comes to launching a post-earthquake reconstruction program. The strategy should be reasonable and should consider the best interests of everyone affected; self-help and imported fabrication should play no part in the decision-making procedures. Creating awareness, physically demonstrating options and delivering are the three steps for the success of reconstruction programs. The extent of affected area and the magnitude of earthquakes are variable in nature and it is on these two aspects that the reconstruction strategy is devised. Technical aspects are focused towards the development of the affected areas and conceptual design of surrounding neighborhoods. It also aims at identifying seminars and programs based on easy financing for a new home. Along with these, review processes are conducted for the analysis of new residential needs based on optimizing the use of available land for planning and development. The paper discusses the construction of housing and resettlements as prioritized activities that must be undertaken post an earthquake. Earthquakes physically only destroy structures and buildings but for the people affected, they destroy lives, jobs, companies, sources of food and the sense of safety and traumatize the ones who come out alive.