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This study shows density functional theory (DFT) investigations that 3d transition metals (TM) doping in silicene can greatly alter the geometric, spintronic, and optoelectronic properties of the pristine silicene (p‐Si) layer. Significant Bader charge transfer from 3d TM atoms to surrounding Si atoms ensures the tight bonding between dopant and substrate; hence, all the 3d transition metal‐doped silicene (3d TM‐Si) systems are said geometrically strong and stable. Sc‐ and Ti‐doped systems show the lowest formation energies of −84.72 and −84.21 eV, respectively, while Zn‐Si bears the highest (−70.89 eV). 3d TMs from V to Co doping induces magnetic moment (MM) in the silicene layer which mainly comes from d‐orbitals of 3d TM atoms and partly from p‐orbitals of Si atoms, meanwhile Mn‐Si has MM as high as 3.0 μB. Among 3d TM‐Si systems studied, Cr‐Si and Mn‐Si systems became half metals, Ti‐Si became indirect semiconductor, whereas rest others convert into metals. Sc and V doping is found to be p‐type doping as the Fermi level shifts into the valence band. Moreover, multiple and broader peaks in the absorption coefficient plot indicate the significant photoabsorption of 3d TM‐Si systems. The present study of electronic, magnetic, and optical properties of 3d TM‐Si systems extend a helpful proposal for further experimental work to fabricate silicene‐based single‐spin electron source and other nano‐electronic devices.

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Pakistan has been facing an energy crisis for many years. Techno-economic analysis of wind power generation is carried out to meet energy demand. Wind data from 2016 to 2018 has been selected for a coastal site of Sindh, Pakistan. For this purpose, four distribution functions, namely Weibull, Gamma, Rayleigh, and Lognormal are used. These distribution functions are compared using the coefficient of determination (R 2 ) and root mean square error tests. Wind potential on a daily, monthly, yearly and seasonal basis is evaluated. In this regard, various turbine models are selected to estimate their power generation capacity. The assessment results for a hub height of 100 m shows the average wind speed for three years is 7.9 m/s with direction dominated between the West and Southwest. The most probable wind speed is 9.5 m/s having a maximum energy density of 455 kWh/m 2 in May. The maximum mean wind speed of 8.55 m/s is in the spring. The Weibull distribution function (k = 2.92 & C = 8.86 m/s) performs the best. The maximum capacity factor for Fuhrlander LLC WTU 3.0-120 is 55.49% and for Siemens SWT-3.15-142 is 55.22%. Likewise, the estimated lowest LCOE ($/1kWh) for Fuhrlander LLC WTU 3.0-120 and Siemens SWT-3.15-142 is $0.04016 and $0.04035 respectively. Thus, this site contains suitable technical and economic characteristics of the wind power plant. KeywordsAnnual energy generation • Capacity factor • Cost of energy generation • Cumulative and probability distribution functions • Wind power and energy densities * Kalsoom Bhagat