Symbiosis of artificial intelligence and fuel-free power generation Neutrinovoltaic

The role of artificial intelligence (AI) in the modern world is becoming increasingly important. It is obvious that the next stage of technological development of mankind will be closely connected with AI. Countries that actively implement AI will be able to achieve significant success in the competitive struggle and secure leading positions in future economic development.

Artificial intelligence (AI) is able to model, predict and optimize the behavior of materials at the microscopic level, which is inaccessible to a conventional microscope. However, the development of AI and the functioning of data processing centers (DPC) require a huge amount of stable electricity, and this is becoming a serious problem, since most countries have a shortage of electricity and its transmission systems.

This situation is also observed in Russia. Indirect evidence of problems with power supply is the information published on the portal "Atomic Energy" by the CEO of PSM Andrey Medvedev that the total capacity of diesel generator units (DGU) for data centers (DC) produced by PSM has increased by more than a third over the past year, to 88 MW, and the demand for them in the energy solutions market is constantly growing.

For now, solving power supply issues with the help of DGUs remains a forced step due to the lack of other options. However, in the medium term, new, including fuel-free, methods of power supply will appear, including data centers. We are talking about fuel-free graphene generators-resonators developed by the Neutrino Energy group of companies. These devices convert the energy of particles of surrounding fields of invisible radiation (Louis de Broglie matter waves) and the thermal motion of graphene atoms into electric current. Neutrino Energy is currently testing its fuel-free generators Neutrino Power Cubes. However, an unexpected problem arose: such devices did not exist before, and there are no approved standards for their certification. Therefore, the company, together with certification bodies, is developing the regulations for the necessary tests and the corresponding documentation.

Holger Thorsten Schubart, President of the Neutrino Energy Group

Artificial intelligence has become a key element of modern progress. However, its widespread use is associated with a serious problem - high energy consumption. Large-scale models and logical inference systems require a stable and uninterruptible power supply for their operation. Against this background, the Neutrino Energy group of companies presented an innovative approach based on Neutrinovoltaic technology. Unlike traditional renewable sources, which are weather-dependent and unstable, Neutrinovoltaic devices create a constant electric current due to the dynamic behavior of graphene and the resonance process of its atoms under the influence of Louis de Broglie matter waves in special nanomaterials. These properties are ideal for the needs of AI, which requires an uninterruptible, stable and localized supply of energy. This energy innovation is based on multilayer nanostructures made of graphene and doped silicon. Graphene atoms vibrate under the influence of neutrinos, cosmic rays and ambient radiation, creating mechanical vibrations in resonance. Due to the dynamic behavior of graphene, expressed in the form of "graphene waves", the interaction of electric and magnetic fields occurs and EMF occurs. Unlike photovoltaic panels, which use photons and depend on the length of daylight, these nanostructures work regardless of the weather or solar radiation day and night.

Currently, scientists from the Neutrino Energy group of companies continue to work on optimizing the Neutrinovoltaic technology in order to maximize the resonance of the oscillations of "graphene waves". Any change in the structure of atoms, the selection of the concentration of alloying elements or the thickness of the layer affects the conversion of oscillations into electric current. The optimization zone is incredibly vast and complex for traditional trial and error experiments. In such conditions, AI becomes an indispensable tool. It is able to simulate millions of options and predict the results, which reduces research time.

Artificial intelligence allows you to simulate the behavior of particles in nanostructures and predict how small changes in geometry or composition affect oscillations. Machine learning algorithms based on experimental data find hidden patterns and indicate optimal parameters for enhancing resonance.

Generative models open up new horizons, offering innovative architectures that would be impossible to create using traditional optimization methods. Reinforcement learning allows for endless virtual trials, discarding unsuccessful options and narrowing the range of effective configurations. The result is designs that are ideal for mass production and have high performance. Neutrino Energy Group works with scientific institutions to introduce artificial intelligence into the design process. This significantly accelerates the development of new technologies compared to traditional laboratory methods.

This AI-powered approach is not only efficient. It also saves money by reducing the number of failed prototypes and increases reliability by moving projects closer to predictable and repeatable results. Thanks to AI, energy supply becomes safer, which accelerates, improves and makes the development of neutrinovoltaic materials more accurate.

The role of AI is the ability to explore a huge space of nanomaterial configurations with high accuracy and speed. This turns uncertain experiments into controlled, data-driven engineering. Neutrinovoltaics, in turn, ensures sustainability due to continuous operation in any environmental conditions, the absence of moving parts and the generation of energy directly at the point of use. This avoids systemic vulnerability. Endurance tests of fuel-free Neutrino Power Cubes generators show the sustainability of their operation, which is based on specific properties. Together, these properties create tandem sustainability that exceeds the sustainability of each system separately. It is worth noting that the risk of stagnation in the development of neutrinoenergetics, an extremely complex field of physics and materials science, is reduced by the computing capabilities of AI, which accelerates discoveries.

Neutrino Power Cubes are compact generators with a capacity of 5 to 6 kW, which embody the idea of ​​local stability. Instead of transmitting energy through power lines, where losses and failures are inevitable, these devices generate direct current electricity directly at the point of use. For the AI ​​infrastructure, this means independence from remote network nodes and a stable power supply.

The solid-state nature of Neutrinovoltaic systems is key. They have no moving parts, which eliminates the typical degradation mechanisms inherent in turbines or piston engines. This reliability ensures that AI systems are protected from failures and ensures that they are powered by sources that require minimal maintenance. Energy stability directly affects the stability of computing processes.

Artificial intelligence and neutrino energy do not just go hand in hand. They mutually support each other, creating a synergistic effect. Instead of one technology replacing another, they develop together, enriching each other with new capabilities.

The example of the Neutrino Energy group of companies shows how advanced technologies in the field of artificial intelligence and energy are harmoniously combined. As a result, we do not just get a new energy source or a computing tool, but a new paradigm of technological evolution based on mutual support and high accuracy.

Author: Rumiantcev L.K.

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