Carbon Capture

In a significant stride towards advancing carbon capture and storage (CCS) technologies, researchers have demonstrated the potential of flexible metal-organic framework (MOF) films for efficient, reversible CO2 capture and release at low pressures. T

In a significant stride towards more efficient and cost-effective carbon capture, researchers at the University of Houston have developed a membraneless system that could revolutionize how we approach point-source carbon emissions. Published in the j

In the pursuit of a low-carbon future, accurate prediction of power system carbon emissions is becoming increasingly vital. A recent study published in the journal *Discover Artificial Intelligence* introduces a novel method that could significantly

In the quest for cleaner water and more sustainable energy solutions, a team of researchers led by Madina Bissenova from Satbayev University has made significant strides. Their work, recently published in the journal “Materials for Renewable and Sust

In the relentless pursuit of carbon neutrality, researchers have unveiled a groundbreaking carbon capture system that could reshape the energy sector’s approach to emissions reduction. Published in the journal *Discover Applied Sciences*—translated f

In a groundbreaking study published in the journal *Nature Scientific Reports*, researchers have harnessed the power of deep learning to predict the mechanical properties of natural fiber polymer composites with remarkable accuracy. This advancement,

In a groundbreaking development for the energy sector, researchers have harnessed the power of advanced machine learning techniques to predict carbon dioxide (CO2) adsorption in KOH-activated biochar with unprecedented accuracy. This innovation, led

In the quest to optimize oil recovery while mitigating carbon emissions, a groundbreaking study has emerged from the Key Laboratory for EOR Technology at Northeast Petroleum University. Led by Miaoxin Zhang, the research delves into the intricate dan

In the quest to curb carbon emissions, scientists are turning to machine learning to optimize a critical process: geological sequestration of CO2. A recent study published in the journal *Nature Scientific Reports* by Kashif Liaqat and colleagues fro

In a significant stride towards understanding and mitigating urban carbon emissions, a team of researchers led by Ying Tian from the State Key Laboratory of Electrical Insulation and Power Equipment at Xi’an Jiaotong University has developed a novel