AI-driven fusion is the next step for fusion research.

"Researchers at the Princeton Plasma Physics Laboratory are harnessing artificial intelligence and machine learning to enhance fusion energy production, tackling the challenge of controlling plasma reactions. Their innovations include optimizing the design and operation of containment vessels and using AI to predict and manage instabilities, significantly improving the safety and efficiency of fusion reactions. This technology has been successfully applied in tokamak reactors, advancing the field towards viable commercial fusion energy. Credit: SciTechDaily.com" (ScitechDaily, AI-Powered Fusion: The Key to Limitless Clean Energy)

The next-generation fusion systems use AI to control the environment. In Tokamak-type fusion reactors, the plasma, temperature is far higher than the Sun's core orbits in a donut shape accelerator. The plasma hovers in a magnetic field, that presses it in the shape of wire. 

When the system ignites the fusion the ignition lasers or opposite pole plasma will inject into the reactor. The problem is that in the flashpoint. When fusion starts in the middle of the plasma ring, the energy travels out from the plasma ring. Push it outside. The fusion energy destroys the plasma ring if it travels from the inside out. 

But if the fusion starts on the plasma ring's shell. it starts to push plasma into its form. In that system, the fusion reactor must create two internal, positive (ion) and negative (anion) plasma rings, and then drive them together. The idea is that the fusion starts in the shell of the internal plasma ring. The problem is how to control those plasma rings. 

The system should begin the fusion symmetrically in the outer shell of the plasma ring. In that case, fusion transfers energy in the plasma from its shell. And that energy keeps the plasma in its form. 

The ion-anion fusion. Where the system puts ions impact with anions could be promising. 

One of the theoretical systems that can be promising is the so-called double Tokamak, where the toruses or plasma rings in them touch each other. 

In the first ring the positive, and the second ring or reactor, the negative plasma orbits in the intensive heat and magnetic pressure. Then the system drives those plasma rings against each other. But making that system practical is difficult. The system must control those plasma rings with very high accuracy. The problem is how to control the contact points. and keep those plasma rings separated before the ignition starts. 

Double-tokamak-reactors model. In that case reactor system has two impact points. The ion plasma orbits in another and anion plasma orbits in another ring. The problem is how to control those ion and anion flows. And deny their impact too early. 

In some other systems, two linear accelerators will shoot positive or ion plasma against the negative, or anion plasma. When those accelerators shoot ions against anions at quite high speed, and the system aims for microwaves and lasers at the impact point, the system can create fusion. The only difference between double tokamak and linear fusion reactors is the shape of the accelerator. 

The temperature in the fusion system is higher than in the Sun. And that means the reactor must control that intense plasma with very high accuracy. And if the plasma comes too close to the reactor's shell. It burns a hole in the reactor immediately. In that case, the high-energy plasma causes the same effect as a hydrogen bomb. 

The fusion system offers a limitless energy solution but if the system cannot predict the situation, where plasma comes too close to the reactor's shell, that thing can cause destruction. The AI can control the reactor's magnets. And things like ignition systems. If those systems are not accurate enough, that destroys the plasma structure. 

https://scitechdaily.com/ai-powered-fusion-the-key-to-limitless-clean-energy/