Nuclear

In a significant advancement for medical diagnostics, researchers have unveiled a deep learning model designed to enhance the analysis of two crucial histopathological markers: the nuclear protein Ki-67 and tumor-infiltrating lymphocytes (TILs). This

Recent advances in plasma physics could have significant implications for the future of energy generation, particularly in the realm of nuclear fusion. A new study led by W.Q. Ma from the Institutes of Physical Science and Information Technology at A

In a groundbreaking study, researchers at the CIMPLE-PSI Laboratory in India have delved into the complexities of tungsten’s recrystallization behavior under extreme conditions, a topic of critical importance for the future of fusion energy. As the w

Recent research published in the journal ‘Nuclear Fusion’ has unveiled intriguing insights into the behavior of energetic particles in tokamak plasmas, particularly focusing on the effects of zonal fields on reversed-shear Alfvén eigenmodes. The stud

In a groundbreaking study published in “Nuclear Materials and Energy,” researchers have explored the intricacies of boronization, a wall conditioning technique pivotal for enhancing plasma performance in fusion devices. This research, led by Huace Wu

Recent research published in the journal ‘Nuclear Fusion’ has shed light on the complex dynamics of turbulence in the divertor region of tokamaks, a crucial area for the successful operation of fusion reactors. The study, led by C. Wüthrich from the

In a groundbreaking development for the field of fusion energy, researchers have harnessed the power of machine learning to enhance the understanding and control of turbulent transport in plasma. This innovative research, led by H. Li from the Key La

In a groundbreaking study published in ‘Scientific Reports,’ researchers have harnessed the power of machine learning to revolutionize the way we understand and track turbulent structures in plasma fusion devices. Led by Sarah Chouchene from the

In a significant advancement for the nuclear fusion sector, researchers have unveiled a machine learning framework that could revolutionize the design and longevity of in-vessel components critical to fusion reactors. Led by Bin Zhu from the School o

In a significant advancement for nuclear fusion technology, researchers at the Korea Atomic Energy Research Institute (KAERI) have conducted a comprehensive safety analysis of the Helium Cooled Ceramic Reflector (HCCR) blanket, a critical component i