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Smart glass has a bright future

 E-Mail IMAGE: SEM micrograph of vertically standing, flat micromirror array with an inset of magnified area. Credit: Hillmer et al. view more  Credit: Hillmer et al. Buildings are responsible for 40 percent of primary energy consumption and 36 percent of total CO2 emissions. And, as we know, CO2 emissions trigger global warming, sea level rise, and profound changes in ocean ecosystems. Substituting the inefficient glazing areas of buildings with energy efficient smart glazing windows has great potential to decrease energy consumption for lighting and temperature control. Harmut Hillmer et al. of the University of Kassel in Germany demonstrate that potential in MOEMS micromirror arrays in smart windows for daylight steering, a paper published recently in the inaugural issue of the

Polarized photovoltaic properties emerge

 E-Mail IMAGE: Tungsten selenide (WSe2) and black phosphorus (BP) do not exhibit polarized electronic behavior until combined such that their structures overlap. view more  Credit: ©2021 Ideue et al. For the first time, researchers have discovered a way to obtain polarity and photovoltaic behavior from certain nonphotovoltaic, atomically flat (2D) materials. The key lies in the special way in which the materials are arranged. The resulting effect is different from, and potentially superior to, the photovoltaic effect commonly found in solar cells. Solar power is considered a key technology in the move away from fossil fuels. Researchers continually innovate more efficient means to generate solar energy. And many of these innovations come from the world of materials research. Research Associate Toshiya Ideue from the University of Tokyo s Department of Applied Physics and his team are interested in the photovoltaic properties of 2D materials and their interfaces where

From dinner to sustainable electronics, the surprising versatility of crabs

Osaka University researchers have developed 3D porous nanocarbon materials through the pyrolysis of chitin nanofiber papers derived from crab shells. The properties of the pyrolyzed chitin nanofiber papers could be controlled using the pyrolysis temperature, and the materials were successfully used as photosensors, as well as supercapacitor electrodes for energy storage. It is hoped that the high performance achieved using the renewable raw material will highlight the viability of sustainable electronics.

Solar cells: Losses made visible on the nanoscale

 E-Mail IMAGE: A conductive AFM tip is used to scan the sample surface of an a-Si:H/c-Si interface under ultra-high vacuum on the nm scale, revealing the transport channels of the charge carriers. view more  Credit: Martin Künsting /HZB Silicon solar cells are now so cheap and efficient that they can generate electricity at prices of less than 2 cent/kWh. The most efficient silicon solar cells today are made with less than 10 nanometres thin selective amorphous silicon (a-Si:H) contact layers, which are responsible for separating the light-generated charges . Efficiencies of over 24% are achieved at HZB with such silicon heterojunction solar cells and are also part of a tandem solar cell that lead to a recently reported efficiency record of 29.15 % (A. Al-Ashouri, et al.

Crystal structure prediction of multi-elements random alloy

Credit: POSTECH Alchemy, which attempted to turn cheap metals such as lead and copper into gold, has not yet succeeded. However, with the development of alloys in which two or three auxiliary elements are mixed with the best elements of the times, modern alchemy can produce high-tech metal materials with high strength, such as high entropy alloys. Now, together with artificial intelligence, the era of predicting the crystal structure of high-tech materials has arrived without requiring repetitive experiments. A joint research team of Professor Ji Hoon Shim and Dr. Taewon Jin (first author, currently at KAIST) of POSTECH s Department of Chemistry, and Professor Jaesik Park of POSTECH Graduate School of Artificial Intelligence have together developed a system that predicts the crystal structures of multi-element alloys with expandable features without needing massive training data. These research findings were recently published in

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