Review on Metallization in Crystalline Silicon Solar Cells

Solar cell market is led by silicon photovoltaics and holds around 92% of the total market. Silicon solar cell fabrication process involves several critical steps which affects cell efficiency to large extent. This includes surface texturization, diffusion, antireflective coatings, and contact metallization. Among the critical processes, metallization is more significant. By optimizing contact metallization, electrical and optical losses of the solar cells can be reduced or controlled. Conventional and advanced silicon solar cell processes are discussed briefly. Subsequently, different metallization technologies used for front contacts in conventional silicon solar cells such as screen printing and nickel/copper plating are reviewed in detail. Rear metallization is important to improve efficiency in passivated emitter rear contact cells and interdigitated back contact cells. Current models on local Al contact formation in passivated emitter rear contact (PERC) cells are reviewed, and the influence of process parameters on the formation of local Al contacts is discussed. Also, the contact mechanism and the influence of metal contacts in interdigitated back contact (IBC) cells are reviewed briefly. The research highlights on metallization of conventional screen printed solar cells are compared with PERC and IBC cells

A Framework for Biomechanical Analysis of Jump Landings for Injury Risk Assessment

Competitive sports require rapid and intense movements, such as jump landings, making athletes susceptible to injuries due to altered neuromuscular control and joint mechanics. Biomechanical features during landings are associated with injury risk, emphasizing proper movement and postural stability. Computer vision techniques offer a time-efficient, noninvasive, and unbiased method to assess jump-landings and identify injury risks. This study proposes a video analysis framework to evaluate jump landing biomechanics in athletes todetermineirregularmovementsandincorrectpostures.It providesadviceandrecommendationstocoachesforinjury predictionandtrainingimprovements.Theproposedframework istestedusingcountermovementjumpvideosof17NCAA DivisionIfemalebasketballathletes.Theresultsindicateda lowMeanAbsoluteError(0.97),highcorrelation(0.89),high averageaccuracy(98.31%)andF1score(0.98),signifyingthe framework’sreliabilityinidentifyinginjuryrisk