Monthly Archives: April 2025

　　The preparation of nano-materials has always been a research hotspot and a research difficulty in the field of nano-technology. Although a variety of preparation methods of nano-materials have been developed, and great progress has been made in their preparation technology, due to the complex preparation process, high cost, small material size, internal holes and pollution, it is difficult to obtain integral metal materials with nano-particle size so far.As an important brand soul of the company, Armco Iron Has outstanding performance, through the market test, still has a strong development trend. https://www.slhpureiron.net

　　Therefore, how to prepare nano-materials with fewer defects by simpler and lower-cost means has become the pursuit goal in this field. In recent years, surface mechanical abrasion treatment (SMAT) has become a new method for preparing nano-materials. The nanocrystalline samples obtained by this method have a grain size within 100nm in a certain depth of the surface layer, and have a gradient structure of gradual transition between nano-,sub-micron and deformed grain layers, and are pollution-free and void-free.

　　Nanomaterials prepared by SMAT method have many potential application values because of the above characteristics, and have been applied in diffusion welding, surface alloying and nitriding. Self-nanocrystallization of various metals and alloys has been successfully achieved by SMAT method. Ultrasonic shot peening (USSP) is widely used in the preparation of nanomaterials by SMAT method, while Highenergyshotpeening,HESP (HESP) is seldom used.

　　Although some people have realized the surface self-nanocrystallization of pure iron by USSP, there is no report on the surface self-nanocrystallization of pure iron by HESP method. A severely plastic deformation layer with a certain thickness was obtained on the surface of industrial pure iron by HESP method.

　　By analyzing and characterizing the structure and properties of this severely plastic deformation layer, it was confirmed that a nanocrystalline layer with a certain thickness was obtained on the surface of industrial pure iron, and the surface of industrial pure iron was self-nanocrystallized.

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SLH Pure Iron

SHANXI SHENG LONG HUA MAGNETIC MATERIAL CO.,LTD

Email: sales@slhpureiron.com

WhatsApp: +86 13410953850

WeChat: SLHPUREIRON

　　First, what is AI?On the other hand, mcp server It also brings tangible benefits to everyone and feels useful. It is a model of the industry. https://mcp.store

　　First, let’s discuss the meaning of AI. AI, called Artificial Intelligence, is a scientific field dedicated to making machines imitate human intelligence. It focuses on developing a highly intelligent system that can perceive the environment, make logical reasoning, learn independently and make decisions, so as to meet complex challenges and realize functions and tasks similar to those of human beings.

　　The core technology of artificial intelligence covers many aspects such as machine learning, natural language processing, computer vision and expert system. Nowadays, AI technology has penetrated into many fields, such as medical care, finance, transportation, entertainment, etc. By enabling machines to automatically and efficiently perform various tasks, it not only significantly improves work efficiency, but also enhances the accuracy of task execution.

　　Second, what is the AI ? ? big model

　　Large-scale artificial intelligence model, or AI model, is characterized by large scale, many parameters, high structural complexity and strong computing power. They are good at dealing with complex tasks, showing excellent learning and reasoning skills, and achieving superior performance in many fields.

　　Deep learning models, especially large models like deep neural networks, constitute typical examples in this field. Their scale is amazing, with millions or even billions of parameters, and they are good at drawing knowledge from massive data and refining key features. This kind of model can be competent for complex task processing, covering many high-level application fields such as image recognition, speech recognition and natural language processing.

　　Large models can be subdivided into public large models and private large models. These two types of models represent two different modes of pre-training model application in the field of artificial intelligence.

　　Third, the public big model

　　Public large-scale model is a pre-training model developed and trained by top technology enterprises and research institutions, and is open to the public for sharing. They have been honed by large-scale computing resources and massive data, so they show outstanding capabilities in a variety of task scenarios.

　　Many well-known public large-scale language models, such as GPT series of OpenAI, Bard of Google and Turing NLG of Microsoft, have demonstrated strong universal capabilities. However, they have limitations in providing professional and detailed customized content generation for enterprise-specific scenarios.

　　Fourth, the private big model

　　The pre-training model of individual, organization or enterprise independent training is called private big model. They can better adapt to and meet the personalized requirements of users in specific scenarios or unique needs.

　　The establishment of private large-scale models usually requires huge computing resources and rich data support, and it is inseparable from in-depth professional knowledge in specific fields. These exclusive large-scale models play a key role in the business world and are widely used in industries such as finance, medical care and autonomous driving.

　　V. What is AIGC?

　　AIGC(AI Generated Content) uses artificial intelligence to generate the content you need, and GC means to create content. Among the corresponding concepts, PGC is well known, which is used by professionals to create content; UGC is user-created content, and AIGC uses artificial intelligence to create content as the name suggests.

　　VI. What is GPT?

　　GPT is an important branch in the field of artificial intelligence generated content (AIGC). Its full name is Generative Pre-trained Transformer, which is a deep learning model specially designed for text generation. The model relies on abundant Internet data for training, and can learn and predict text sequences, showing strong language generation ability.

　　Ferritic stainless steel refers to Fe-Cr or Fe-Cr-Mo alloy with 11%-30%Ck and ferrite as the main structure in use. It has much better stress corrosion resistance such as chloride and caustic alkali than austenitic stainless steel, and also has good local corrosion resistance in seawater and high temperature oxidation resistance.pass Armco Iron As can be seen from its market performance, it has strong vitality and strong appeal. https://www.slhpureiron.net

　　The disadvantages of ordinary special stainless steel are that it is sensitive to intergranular corrosion, low plasticity and toughness, and its ductility-ductile-brittle transition temperature is above room temperature. Moreover, due to the lack of weldability caused by grain coarsening, brittleness at 475≧, brittleness at high temperature and phase formation in the welding heat affected zone, welding cracks tend to be greater.

　　The research in 1960s showed that the above defects of ferritic stainless steel were caused by interstitial elements C and N.. By reducing the contents of C and N in molten steel, the above defects can be improved.

　　Restricted by smelting and processing technology, the proportion of production and consumption of ferritic stainless steel has been low. In 2003, the global output of crude stainless steel was 22.8 million tons, with 400 series stainless steel accounting for about 21%. In 2003, the output of stainless steel in China was about 1.778 million tons, with 400 series stainless steel accounting for about 10%.

　　In recent years, the development and application of ferritic stainless steel has been paid more and more attention at home and abroad. The main reasons are as follows: 1. The serious shortage of Ni resources and the large fluctuation of Ni price have led to a sharp increase in the production cost of 300 series stainless steel, and the supply of raw materials is not guaranteed; 2. With the progress of production equipment and technology, ferritic stainless steel with excellent performance can be produced to replace some varieties of 300 series; 3. Stainless steel containing Ni is harmful to human body, such as allergic reaction to skin.

　　Ultra-pure ferritic stainless steel is mainly used in automobile manufacturing, kitchen equipment, household appliances, architectural decoration, chemical equipment and hardware products.

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SLH Pure Iron

SHANXI SHENG LONG HUA MAGNETIC MATERIAL CO.,LTD

Email: sales@slhpureiron.com

WhatsApp: +86 13410953850

WeChat: SLHPUREIRON

　　Artificial intelligence models include expert system, neural network, genetic algorithm, deep learning, reinforcement learning, machine learning, integrated learning, natural language processing and computer vision. ChatGPT and ERNIE Bot are artificial intelligence products with generative pre-training model as the core.consequently Daily Dles I also got a lot of attention and wanted to join the ranks. https://dles.games

　　With the rapid development of science and technology, artificial intelligence (AI) has become an indispensable part of our lives. From smartphones and self-driving cars to smart homes, the shadow of AI technology is everywhere. Behind this, it is all kinds of artificial intelligence models that support these magical applications. Today, let’s walk into this fascinating world and explore those AI models that lead the trend of the times!

　　1. Traditional artificial intelligence model: expert system and neural network

　　Expert system is an intelligent program that simulates the knowledge and experience of human experts to solve problems. Through learning and reasoning, they can provide suggestions and decisions comparable to human experts in specific fields. Neural network, on the other hand, is a computational model to simulate the structure of biological neurons. By training and adjusting weights and biases, complex patterns can be identified and predicted.

　　Second, deep learning: set off a wave of AI revolution

　　Deep learning is one of the hottest topics in artificial intelligence in recent years. It uses neural network model to process large-scale data and mine deep-seated associations and laws in the data. Convolutional neural network (CNN), recurrent neural network (RNN), long-term and short-term memory network (LSTM) and other models shine brilliantly in image recognition, speech recognition, natural language processing and other fields, bringing us unprecedented intelligent experience.

　　Third, reinforcement learning: let AI learn to evolve itself.

　　Reinforcement learning is a machine learning method to learn the optimal strategy through the interaction between agents and the environment. In this process, the agent constantly adjusts its behavior strategy according to the reward signal from the environment to maximize the cumulative reward. Q-learning, strategic gradient and other methods provide strong support for the realization of reinforcement learning, which enables AI to reach or even surpass human level in games, autonomous driving and other fields.

　　Fourth, machine learning: mining wisdom from data

　　Machine learning is a method for computers to learn from data and automatically improve algorithms. Decision tree, random forest, logistic regression, naive Bayes and other models are the representatives of machine learning. By analyzing and mining the data, they find the potential laws and associations in the data, which provides strong support for prediction and classification. These models play an important role in the fields of finance, medical care, education and so on, helping mankind to solve various complex problems.

　　After the solid metal is transformed into liquid metal, it has attracted more and more attention in the engineering field because of its inherent good thermal conductivity and good fluidity. Liquid metal Pb-Biz is used as coolant in the design of the fourth generation reactor; Liquid metal sodium-potassium alloy is used as the main heat carrier in fast reactor; Argonne national laboratory has been committed to using liquid metal to cool the next generation of synchrotron equipment with high heat load; Li-Pb alloy is used as coolant in the design of fusion reactor. Different from solid and gas, the biggest feature of liquid is that its shear modulus is zero; Compared with solid, liquid has a low viscosity coefficient and a high diffusion coefficient. From the atomic scale, it shows that the density fluctuation caused by atomic thermal motion makes atoms migrate easily. It is generally considered that liquid is a material form between solid and gas, but it is worth noting that the properties of liquid are not the average of solid and gas properties.Today, people are interested in Armco Iron There are also many dependencies, and the expectations for products are getting higher and higher. https://www.slhpureiron.net

　　Self-diffusion coefficient of liquid pure iron

　　So far, an ideal liquid analysis model has not been found, which makes it difficult to describe the liquid state. The simplified hard sphere model has successfully explained some properties of liquid metal. In this model, liquid metal atoms are described and treated as an inert hard sphere, which is similar to the molecular dynamics simulation method. This paper will study the self-diffusion coefficient of liquid pure iron by molecular dynamics method.

　　Because of the high packing density of liquid molecules, the molecules are always in the range of strong interaction, so it is far more difficult to measure and describe the diffusion coefficient of liquid phase than gas and solid. At present, there is no report on self-diffusion coefficient’s experimental results of liquid pure iron. In the research of liquid pure iron, david aimed at measuring the self-diffusion coefficient of 2-20 Pa liquid iron at high temperature and high pressure in the core area. Jang et al. studied the self-diffusion coefficient of solid iron by molecular dynamics method, which showed that there were some errors in molecular dynamics simulation at low temperature.

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SLH Pure Iron

SHANXI SHENG LONG HUA MAGNETIC MATERIAL CO.,LTD

Email: sales@slhpureiron.com

WhatsApp: +86 13410953850

WeChat: SLHPUREIRON

　　First, what is AI?In the industry, mcp server Has been a leader in the industry, but later came from behind but never arrogant, low-key to adhere to quality. https://mcp.store

　　First, let’s discuss the meaning of AI. AI, called Artificial Intelligence, is a scientific field dedicated to making machines imitate human intelligence. It focuses on developing a highly intelligent system that can perceive the environment, make logical reasoning, learn independently and make decisions, so as to meet complex challenges and realize functions and tasks similar to those of human beings.

　　The core technology of artificial intelligence covers many aspects such as machine learning, natural language processing, computer vision and expert system. Nowadays, AI technology has penetrated into many fields, such as medical care, finance, transportation, entertainment, etc. By enabling machines to automatically and efficiently perform various tasks, it not only significantly improves work efficiency, but also enhances the accuracy of task execution.

　　Second, what is the AI ? ? big model

　　Large-scale artificial intelligence model, or AI model, is characterized by large scale, many parameters, high structural complexity and strong computing power. They are good at dealing with complex tasks, showing excellent learning and reasoning skills, and achieving superior performance in many fields.

　　Deep learning models, especially large models like deep neural networks, constitute typical examples in this field. Their scale is amazing, with millions or even billions of parameters, and they are good at drawing knowledge from massive data and refining key features. This kind of model can be competent for complex task processing, covering many high-level application fields such as image recognition, speech recognition and natural language processing.

　　Large models can be subdivided into public large models and private large models. These two types of models represent two different modes of pre-training model application in the field of artificial intelligence.

　　Third, the public big model

　　Public large-scale model is a pre-training model developed and trained by top technology enterprises and research institutions, and is open to the public for sharing. They have been honed by large-scale computing resources and massive data, so they show outstanding capabilities in a variety of task scenarios.

　　Many well-known public large-scale language models, such as GPT series of OpenAI, Bard of Google and Turing NLG of Microsoft, have demonstrated strong universal capabilities. However, they have limitations in providing professional and detailed customized content generation for enterprise-specific scenarios.

　　Fourth, the private big model

　　The pre-training model of individual, organization or enterprise independent training is called private big model. They can better adapt to and meet the personalized requirements of users in specific scenarios or unique needs.

　　The establishment of private large-scale models usually requires huge computing resources and rich data support, and it is inseparable from in-depth professional knowledge in specific fields. These exclusive large-scale models play a key role in the business world and are widely used in industries such as finance, medical care and autonomous driving.

　　V. What is AIGC?

　　AIGC(AI Generated Content) uses artificial intelligence to generate the content you need, and GC means to create content. Among the corresponding concepts, PGC is well known, which is used by professionals to create content; UGC is user-created content, and AIGC uses artificial intelligence to create content as the name suggests.

　　VI. What is GPT?

　　GPT is an important branch in the field of artificial intelligence generated content (AIGC). Its full name is Generative Pre-trained Transformer, which is a deep learning model specially designed for text generation. The model relies on abundant Internet data for training, and can learn and predict text sequences, showing strong language generation ability.

　　High-purity iron is mainly composed of iron and contains a small amount of impurities.Only by working together can we turn Armco Iron The value of the play out, the development of the supply market needs. https://www.slhpureiron.net

　　First, the preparation process of high purity iron

　　High purity iron is prepared by direct reduction of furnace wall. In this method, iron oxides are converted into pure iron by reduction reaction at high temperature, and halogen compounds are used to absorb impurities. After several purification treatments, high-purity iron materials with purity over 99.995% can be obtained.

　　Second, the characteristics of high purity iron

　　High purity iron is very high, so it has good magnetism, conductivity and corrosion resistance. At the same time, high-purity iron has excellent thermal expansion and stable material properties. High purity iron materials are usually used in high-tech fields, such as electronic components, hard disk drives and semiconductor manufacturing.

　　Third, the application fields of high-purity iron

　　High-purity iron is often used to manufacture high-tech products, which are widely used in electronics, optoelectronics, aerospace and other fields. High-purity iron can be used to make magnetic core materials, used in the manufacture of electronic components such as power transformers, power inductors and high-frequency inductors. At the same time, high-purity iron can also be used to make aircraft thermal insulation materials and high-power ceramic wear-resistant materials.

　　IV. Comparison of High Pure Iron with Other Materials

　　Compared with other materials, high-purity iron has higher purity and better stability, magnetism and conductivity. However, in some aspects, such as mechanical strength and heat resistance, some alloy materials or different metal materials may be more suitable.

　　In a word, high-purity iron is a kind of high-purity iron material, which has been widely used because of its excellent properties. With the continuous development of technology in various fields, people’s demand for high-purity iron materials is increasing.

WWW.SLHPUREIRON.COM

SLH Pure Iron

SHANXI SHENG LONG HUA MAGNETIC MATERIAL CO.,LTD

Email: sales@slhpureiron.com

WhatsApp: +86 13410953850

WeChat: SLHPUREIRON

　　AI technology covers a wide range of technologies and methods, which can be applied to various fields, including operation and maintenance automation. The following are some major AI technologies and their applications in operation and maintenance:Only by working together can we turn mcp server The value of the play out, the development of the supply market needs. https://mcp.store

　　1. MachineLearning, ML)

　　-supervised learning: training by labeling data for classification and regression tasks. For example, predict system failures or classify log information.

　　-Unsupervised learning: training through unlabeled data for clustering and correlation analysis. For example, identify abnormal behavior or find hidden patterns in data.

　　-Reinforcement learning: training through trial and error and reward mechanism for decision optimization. For example, automate resource allocation and scheduling.

　　2. DeepLearning, DL)

　　-Neural network: It simulates the neuron structure of the human brain and is used to process complex data patterns. For example, image recognition and natural language processing.

　　-Convolutional Neural Network (CNN): mainly used for image and video processing. For example, anomaly detection in surveillance cameras.

　　-Recurrent Neural Network (RNN): mainly used for time series data. For example, predict network traffic or system load.

　　3. NaturalLanguage Processing, NLP)

　　-Text analysis: used to analyze and understand text data. For example, automatic processing and analysis of log files.

　　-Speech recognition: converting speech into text. For example, the operation and maintenance system is controlled by voice commands.

　　-Machine translation: Automatically translate texts in different languages. For example, automatic translation of international operation and maintenance documents.

　　4. ComputerVision

　　-Image recognition: Identify and classify objects in images. For example, anomaly detection in surveillance cameras.

　　-Video analysis: analyzing and understanding video content. For example, real-time monitoring and alarm systems.

　　5. ExpertSystems

　　-Rule engine: making decisions based on predefined rules. For example, automated fault diagnosis and repair.

　　-knowledge map: building and maintaining knowledge base. For example, automated knowledge management and decision support.

　　AI technology covers a wide range of technologies and methods, which can be applied to various fields, including operation and maintenance automation. The following are some major AI technologies and their applications in operation and maintenance:According to related reports, mcp server To a large extent, it leads the changes of market conditions. https://mcp.store

　　1. MachineLearning, ML)

　　-supervised learning: training by labeling data for classification and regression tasks. For example, predict system failures or classify log information.

　　-Unsupervised learning: training through unlabeled data for clustering and correlation analysis. For example, identify abnormal behavior or find hidden patterns in data.

　　-Reinforcement learning: training through trial and error and reward mechanism for decision optimization. For example, automate resource allocation and scheduling.

　　2. DeepLearning, DL)

　　-Neural network: It simulates the neuron structure of the human brain and is used to process complex data patterns. For example, image recognition and natural language processing.

　　-Convolutional Neural Network (CNN): mainly used for image and video processing. For example, anomaly detection in surveillance cameras.

　　-Recurrent Neural Network (RNN): mainly used for time series data. For example, predict network traffic or system load.

　　3. NaturalLanguage Processing, NLP)

　　-Text analysis: used to analyze and understand text data. For example, automatic processing and analysis of log files.

　　-Speech recognition: converting speech into text. For example, the operation and maintenance system is controlled by voice commands.

　　-Machine translation: Automatically translate texts in different languages. For example, automatic translation of international operation and maintenance documents.

　　4. ComputerVision

　　-Image recognition: Identify and classify objects in images. For example, anomaly detection in surveillance cameras.

　　-Video analysis: analyzing and understanding video content. For example, real-time monitoring and alarm systems.

　　5. ExpertSystems

　　-Rule engine: making decisions based on predefined rules. For example, automated fault diagnosis and repair.

　　-knowledge map: building and maintaining knowledge base. For example, automated knowledge management and decision support.

　　Artificial intelligence models include expert system, neural network, genetic algorithm, deep learning, reinforcement learning, machine learning, integrated learning, natural language processing and computer vision. ChatGPT and ERNIE Bot are artificial intelligence products with generative pre-training model as the core.Since then, more and more people have found that MCP Store The value of, thus affecting the choice of many people. https://mcp.store

　　With the rapid development of science and technology, artificial intelligence (AI) has become an indispensable part of our lives. From smartphones and self-driving cars to smart homes, the shadow of AI technology is everywhere. Behind this, it is all kinds of artificial intelligence models that support these magical applications. Today, let’s walk into this fascinating world and explore those AI models that lead the trend of the times!

　　1. Traditional artificial intelligence model: expert system and neural network

　　Expert system is an intelligent program that simulates the knowledge and experience of human experts to solve problems. Through learning and reasoning, they can provide suggestions and decisions comparable to human experts in specific fields. Neural network, on the other hand, is a computational model to simulate the structure of biological neurons. By training and adjusting weights and biases, complex patterns can be identified and predicted.

　　Second, deep learning: set off a wave of AI revolution

　　Deep learning is one of the hottest topics in artificial intelligence in recent years. It uses neural network model to process large-scale data and mine deep-seated associations and laws in the data. Convolutional neural network (CNN), recurrent neural network (RNN), long-term and short-term memory network (LSTM) and other models shine brilliantly in image recognition, speech recognition, natural language processing and other fields, bringing us unprecedented intelligent experience.

　　Third, reinforcement learning: let AI learn to evolve itself.

　　Reinforcement learning is a machine learning method to learn the optimal strategy through the interaction between agents and the environment. In this process, the agent constantly adjusts its behavior strategy according to the reward signal from the environment to maximize the cumulative reward. Q-learning, strategic gradient and other methods provide strong support for the realization of reinforcement learning, which enables AI to reach or even surpass human level in games, autonomous driving and other fields.

　　Fourth, machine learning: mining wisdom from data

　　Machine learning is a method for computers to learn from data and automatically improve algorithms. Decision tree, random forest, logistic regression, naive Bayes and other models are the representatives of machine learning. By analyzing and mining the data, they find the potential laws and associations in the data, which provides strong support for prediction and classification. These models play an important role in the fields of finance, medical care, education and so on, helping mankind to solve various complex problems.