人工智慧融入核融合研究標誌著這兩個領域的關鍵時刻

人工智慧熱潮不斷增長，其與核融合研究的整合標誌著這兩個領域的關鍵時刻。透過解決聚變固有的複雜挑戰，人工智慧有可能大幅縮短實現實用聚變能源的時間。

Artificial intelligence (AI) is playing a pivotal role in advancing nuclear fusion, a promising energy source that has the potential to revolutionize the way we generate power. Here's how AI is impacting the field of nuclear fusion:

人工智慧 (AI) 在推動核融合方面發揮關鍵作用，核融合是一種很有前景的能源，有可能徹底改變我們的發電方式。以下是人工智慧對核融合領域的影響：

1. Controlling Fusion Reactions:

1. 控制聚變反應：

AI is being used to monitor and control fusion reactions in real-time. By analyzing vast amounts of data, AI algorithms can predict and prevent instabilities that can disrupt or terminate fusion processes. This capability enables scientists to maintain stable fusion reactions for longer periods, increasing the efficiency and reliability of the fusion energy generation.

人工智慧被用來即時監控和控制聚變反應。透過分析大量數據，人工智慧演算法可以預測並防止可能破壞或終止融合過程的不穩定性。這種能力使科學家能夠更長時間地維持穩定的聚變反應，從而提高聚變能產生的效率和可靠性。

2. Analyzing Reactor Designs:

2. 分析反應器設計：

Nuclear fusion reactors are highly complex systems, and designing them optimally is crucial for efficient fusion energy generation. AI is being employed to analyze various reactor designs rapidly and identify the most promising configurations. By considering multiple parameters simultaneously, AI algorithms can uncover design aspects that may be overlooked by traditional methods, leading to improved reactor performance.

核融合反應器是高度複雜的系統，優化設計對於有效產生聚變能至關重要。人工智慧被用來快速分析各種反應器設計並確定最有前途的配置。透過同時考慮多個參數，人工智慧演算法可以發現傳統方法可能忽略的設計方面，從而提高反應器效能。

3. Discovering New Alloys:

3. 發現新合金：

Materials used in nuclear fusion facilities must withstand extreme temperatures, radiation, and mechanical stress. Scientists are using AI to identify and develop new alloys that possess the necessary properties for fusion applications. By analyzing atomic-level interactions and predicting material behavior, AI algorithms can accelerate the discovery of high-performance alloys, reducing the time and resources required for materials development.

核融合設施中使用的材料必須能夠承受極端溫度、輻射和機械應力。科學家正在利用人工智慧來識別和開發具有聚變應用所需特性的新合金。透過分析原子級相互作用和預測材料行為，人工智慧演算法可以加速高性能合金的發現，減少材料開發所需的時間和資源。

4. Accelerating Scientific Discoveries:

4. 加速科學發現：

Generating large datasets is essential for training AI algorithms effectively. In the field of nuclear fusion, researchers are creating open-source databases of materials properties calculated using density functional theory (DFT). These datasets, such as the ones compiled by the Oak Ridge National Laboratory (ORNL), enable broader scientific communities to access and utilize materials data for further research and development.

產生大型資料集對於有效訓練人工智慧演算法至關重要。在核融合領域，研究人員正在創建使用密度泛函理論（DFT）計算的材料特性的開源資料庫。這些數據集，例如橡樹嶺國家實驗室 (ORNL) 編制的數據集，使更廣泛的科學界能夠存取和利用材料數據進行進一步的研究和開發。

5. Understanding Material Interactions:

5.了解物質交互作用：

AI is also being applied to gain a deeper understanding of the interactions between materials at the atomic level. By analyzing vast quantities of data generated from quantum chemistry calculations, AI algorithms can identify relationships between molecular structures and their properties. This knowledge is crucial for designing materials with specific functionalities, such as those used in nuclear fusion applications.

人工智慧也被應用於在原子層面上更深入地了解材料之間的相互作用。透過分析量子化學計算產生的大量數據，人工智慧演算法可以識別分子結構及其性質之間的關係。這些知識對於設計具有特定功能的材料至關重要，例如用於核融合應用的材料。

Several companies operating in the AI and nuclear fusion industries are poised to benefit from these technological advancements. Here are a few examples:

幾家從事人工智慧和核融合行業的公司準備從這些技術進步中受益。以下是一些範例：

1. General Electric (GE):

1.通用電氣（GE）：

Through its GE Vernova unit, General Electric is actively engaged in nuclear power research and development. Its initiatives include the application of advanced sensors and imaging techniques to monitor used nuclear fuel materials in real-time, the development of an inspection technology called RADMASS to enhance the cost-effectiveness of reprocessing fuel, and the construction of boiling water nuclear reactors (BWRs).

通用電氣透過其 GE Vernova 部門積極從事核電研究和開發。其舉措包括應用先進感測器和成像技術來即時監測用過的核燃料材料、開發稱為 RADMASS 的檢查技術以提高後處理燃料的成本效益，以及建造沸水核反應器（BWR） ）。

2. IBM (IBM):

2.IBM（國際商業機器）：

While NVIDIA leads the AI and supercomputing sectors with its stock prices surging over 134% this year, IBM is also a प्रमुख player in quantum computing and AI research. The company's quantum computers are cloud-based and accessible for exploration and research purposes.

雖然 NVIDIA 引領人工智慧和超級運算領域，其股價今年飆升超過 134%，但 IBM 也是量子運算和人工智慧研究領域的佼佼者。該公司的量子電腦基於雲，可用於探索和研究目的。

By executing complex simulations on these quantum computers, IBM aims to achieve critical breakthroughs in various industries. A couple of years ago, the company discussed optimizing nuclear power generation through unlocking the value of data in its blog.

透過在這些量子電腦上執行複雜的模擬，IBM 的目標是在各個行業中實現關鍵突破。幾年前，該公司在其部落格中討論了透過釋放數據價值來優化核能發電。

3. ATI Inc. (ATI):

3. 和公司（我們有）：

Specializing in the production of specialty metals and alloys, ATI's expertise aligns well with the demands of fusion reactor applications. The company's High-Performance Materials & Components (HPMC) segment caters to the production of high-performance materials such as titanium and titanium-based alloys used in diverse industries including energy, medical, and aerospace.

ATI 專門生產特殊金屬和合金，其專業知識非常適合聚變反應器應用的需求。該公司的高性能材料和零件（HPMC）部門致力於生產高性能材料，例如用於能源、醫療和航空航天等多種行業的鈦和鈦基合金。

Another segment, Advanced Alloys & Solutions (AA&S), focuses on the production of zirconium and related alloys used in the automotive, electronics, energy, and defense markets.ATI's diverse product portfolio and strong presence in critical industries position the company to benefit from the growing demand for advanced materials in nuclear fusion and other technological sectors.

另一個部門是高級合金和解決方案(AA&S)，專注於生產用於汽車、電子、能源和國防市場的鋯及相關合金。從核融合和其他技術領域對先進材料的需求不斷增長。

As AI continues to advance and its integration into nuclear fusion research deepens, both fields stand to reap significant benefits. By addressing the inherent challenges of fusion and accelerating the path toward practical fusion energy, AI has the potential to contribute to a cleaner, more sustainable, and energy-secure future.

隨著人工智慧的不斷發展及其與核融合研究的整合不斷深入，這兩個領域都將獲得顯著的效益。透過解決聚變的固有挑戰並加速邁向實用聚變能源的道路，人工智慧有潛力為一個更清潔、更永續和能源安全的未來做出貢獻。