Distributed Energy

In a significant advancement for the energy sector, researchers have unveiled a new model for solid oxide fuel cells (SOFCs) that utilize direct internal reforming of ethanol. This innovative approach promises to enhance the efficiency and versatilit

The rapid rise in electric vehicle (EV) adoption has brought forth an urgent need for innovative charging solutions that can keep pace with the increasing demand for charging power. A recent study led by Majid Majidi from the Department of Electrical

In a significant advancement for electrified railways, researchers have introduced a comprehensive compensation method aimed at addressing the persistent issues of negative-sequence and reactive power. This innovative approach, developed by Xiangwu Y

In the rapidly evolving landscape of energy systems, the integration of distributed Renewable Energy Sources (RES) poses significant challenges and opportunities. A recent study led by Christian Rehtanz from TU Dortmund University introduces an innov

In a groundbreaking study published in the journal “Materials & Design,” researchers have unveiled a machine learning framework aimed at predicting the dynamic energy release of high-entropy alloys (HEAs), which are poised to revolutionize the field

In a significant advancement for the energy sector, researchers have unveiled a groundbreaking method to prevent hot cracking in non-weldable nickel-based superalloys, which are critical in high-performance applications such as gas turbines and jet e

Recent research has unveiled the multifaceted role of arginine kinase (AK), an enzyme that could redefine our understanding of energy management in living organisms and its implications for various industries. The study, led by Brenda Martins Vasconc

In a significant advancement for energy efficiency in traditional Ethiopian cooking, researchers have developed an enhanced electric Injera baking pan, known as a mitad, that promises to reduce energy consumption and improve thermal efficiency. This

In a groundbreaking study published in *Results in Engineering*, researchers have unveiled a novel machine learning approach that utilizes an Artificial Protozoa Optimizer (APO) to predict the wear characteristics of copper-zirconia (Cu-ZrO2) nanocom

As the global demand for electricity surges, the integration of renewable energy sources (RES) into power grids is becoming increasingly vital. A recent study led by Raji Krishna from the School of Electrical Engineering at Vellore Institute of Techn