For all of us working with electricity, radioactive waste containment, or hospitals, controlling radioactive processes and predicting their behaviors are key to making our world function safely. Let's look at electricity generation for a quick example of how fission works.
In order to run the turbines of atomic power stations that will eventually bring us our light and internet connections, nuclear power relies on a complicated interplay of atomic interactions, all initiated by the introduction of one neutron into an already stuffed nucleus. Scientists seek to understand how much thermal energy we can extract for the nuclear fission process, and work out what reaction products will be created. After nuclear fission has occurred, nuclei are broken up into smaller parts.
This color map represents the potential energy surface for U-236. The color changes as the excitation energy increases. Researchers used this net of energy relationships to account for the stochastic nature of the Langevin model and represent some key fluctuation-dissipation dynamics associated with Uranium scission points.
Credit: Chikako Ishizuka, Tokyo Institute of Technology
In our researchers' case, the generation of energy is observed from nuclear fission of Uranium-235 (U-235). As a neutron is bombarded into the U-235 nucleus, it produces a Uranium-236 (U-236) nucleus and gives it extra-energy to help it split into two separate fragments. The excitation energy causes the fragmentation, generating atomic energy (see Figure 1).
However, predicting this energetic interaction is difficult, so scientists use simplified models to represent the fragmentation of the nucleus. The Langevin model represents the behavior of dynamic motion of a fissioning nucleus. Previously established Langevin models often considered three dimensions to describe the shape of the nuclei. These included a deformation factor, which describes the various geometries of the two nuclear fragments deformed as a result of fission.
Chikako Ishizuka and Satoshi Chiba at Tokyo Tech, leading this research group, have found that there is an additional factor that influences prediction within a Langevin model, while focusing on U-236. The team's fourth factor considers the deformation of the two separate fragments, rather than assuming the two fragments have the same deformation factor.
Unlike previous 3D Langevin models, the researchers have enhanced the Langevin model to four dimensions so that it can consider the thermal energy of nuclear fragments and consider the individual shape of the fission fragments by taking into account that the heavy and light elements of the fragments behave differently.
The results appear to fit empirical data of nuclear fission better than previously established models. Especially no theoretical models have not reproduced the kinetic energy i.e. the thermal energy of nuclear fission, with predictive power. As seen in Figure 2, the resulting kinetic energy data of the 4D model fits well with observed measurements, in comparison with previous models (shown with the purple and green symbols) without special assumptions.
The Langevin 4D model improves how we can predict low-energy fission and can be used for various nuclei such as poisonous nuclear wastes populated by successively absorbed neutrons starting from uranium. The authors of this work are continuing to develop new applications, with particular emphasis on a future 5D dynamical model that will improve predictive accuracy even further.
Emiko Kawaguchi | EurekAlert!
Tangled magnetic fields power cosmic particle accelerators
14.12.2018 | DOE/SLAC National Accelerator Laboratory
In search of missing worlds, Hubble finds a fast evaporating exoplanet
14.12.2018 | NASA/Goddard Space Flight Center
The more objects we make "smart," from watches to entire buildings, the greater the need for these devices to store and retrieve massive amounts of data quickly without consuming too much power.
Millions of new memory cells could be part of a computer chip and provide that speed and energy savings, thanks to the discovery of a previously unobserved...
What if, instead of turning up the thermostat, you could warm up with high-tech, flexible patches sewn into your clothes - while significantly reducing your...
A widely used diabetes medication combined with an antihypertensive drug specifically inhibits tumor growth – this was discovered by researchers from the University of Basel’s Biozentrum two years ago. In a follow-up study, recently published in “Cell Reports”, the scientists report that this drug cocktail induces cancer cell death by switching off their energy supply.
The widely used anti-diabetes drug metformin not only reduces blood sugar but also has an anti-cancer effect. However, the metformin dose commonly used in the...
A research team from the University of Zurich has developed a new drone that can retract its propeller arms in flight and make itself small to fit through narrow gaps and holes. This is particularly useful when searching for victims of natural disasters.
Inspecting a damaged building after an earthquake or during a fire is exactly the kind of job that human rescuers would like drones to do for them. A flying...
Over the last decade, there has been much excitement about the discovery, recognised by the Nobel Prize in Physics only two years ago, that there are two types...
12.12.2018 | Event News
10.12.2018 | Event News
06.12.2018 | Event News
14.12.2018 | Power and Electrical Engineering
14.12.2018 | Physics and Astronomy
14.12.2018 | Physics and Astronomy