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Machine Learning Potential
Machine-learned interatomic potentials (MLIPs), or simply machine learning potentials (MLPs), are interatomic potentials constructed by machine learning programs. Beginning in the 1990s, researchers have employed such programs to construct interatomic potentials by mapping atomic structures to their potential energies. These potentials are referred to as MLIPs or MLPs. Such machine learning potentials promised to fill the gap between density functional theory, a highly accurate but computationally intensive modelling method, and empirically derived or intuitively-approximated potentials, which were far lighter computationally but substantially less accurate. Improvements in artificial intelligence technology heightened the accuracy of MLPs while lowering their computational cost, increasing the role of machine learning in fitting potentials. Machine learning potentials began by using neural networks to tackle low-dimensional systems. While promising, these models could not systema ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Interatomic Potential
Interatomic potentials are mathematical functions to calculate the potential energy of a system of atoms with given positions in space.M. P. Allen and D. J. Tildesley. Computer Simulation of Liquids. Oxford University Press, Oxford, England, 1989.R. Lesar. Introduction to Computational Materials Science. Cambridge University Press, 2013. Interatomic potentials are widely used as the physical basis of molecular mechanics and molecular dynamics simulations in computational chemistry, computational physics and computational materials science to explain and predict materials properties. Examples of quantitative properties and qualitative phenomena that are explored with interatomic potentials include lattice parameters, surface energies, interfacial energies, adsorption, cohesion, thermal expansion, and elastic and plastic material behavior, as well as chemical reactions.N. W. Ashcroft and N. D. Mermin. Solid State Physics.Saunders College, Philadelphia, 1976.Charles Kittel. Introdu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Carbon
Carbon () is a chemical element; it has chemical symbol, symbol C and atomic number 6. It is nonmetallic and tetravalence, tetravalent—meaning that its atoms are able to form up to four covalent bonds due to its valence shell exhibiting 4 electrons. It belongs to group 14 of the periodic table. Carbon makes up about 0.025 percent of Earth's crust. Three Isotopes of carbon, isotopes occur naturally, carbon-12, C and carbon-13, C being stable, while carbon-14, C is a radionuclide, decaying with a half-life of 5,700 years. Carbon is one of the timeline of chemical element discoveries#Pre-modern and early modern discoveries, few elements known since antiquity. Carbon is the 15th abundance of elements in Earth's crust, most abundant element in the Earth's crust, and the abundance of the chemical elements, fourth most abundant element in the universe by mass after hydrogen, helium, and oxygen. Carbon's abundance, its unique diversity of organic compounds, and its unusual abi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Learning
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of Computational statistics, statistical algorithms that can learn from data and generalise to unseen data, and thus perform Task (computing), tasks without explicit Machine code, instructions. Within a subdiscipline in machine learning, advances in the field of deep learning have allowed Neural network (machine learning), neural networks, a class of statistical algorithms, to surpass many previous machine learning approaches in performance. ML finds application in many fields, including natural language processing, computer vision, speech recognition, email filtering, agriculture, and medicine. The application of ML to business problems is known as predictive analytics. Statistics and mathematical optimisation (mathematical programming) methods comprise the foundations of machine learning. Data mining is a related field of study, focusing on exploratory data analysi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Stainless Steel
Stainless steel, also known as inox, corrosion-resistant steel (CRES), or rustless steel, is an iron-based alloy that contains chromium, making it resistant to rust and corrosion. Stainless steel's resistance to corrosion comes from its chromium content of 11% or more, which forms a Passivation (chemistry), passive film that protects the material and can self-healing material, self-heal when exposed to oxygen. It can be further alloyed with elements like molybdenum, carbon, nickel and nitrogen to enhance specific properties for various applications. The alloy's properties, such as luster and resistance to corrosion, are useful in many applications. Stainless steel can be rolled into Sheet metal, sheets, plates, bars, wire, and tubing. These can be used in cookware, cutlery, surgical instruments, major appliances, vehicles, construction material in large buildings, industrial equipment (e.g., in paper mills, chemical plants, water treatment), and storage tanks and tankers for ch ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Austenitic Stainless Steel
Austenitic stainless steel is one of the five families of stainless steel (along with ferritic, martensitic, duplex and precipitation hardened). Its primary crystalline structure is austenite (face-centered cubic). Such steels are not hardenable by heat treatment and are essentially non-magnetic. This structure is achieved by adding enough austenite-stabilizing elements such as nickel, manganese and nitrogen. The Incoloy family of alloys belong to the category of super austenitic stainless steels. History During World War II, the Schaeffler diagram was invented by Anton, who was then a budding metallurgist in the employ of two American welding electrode manufacturers, Harnischfeger Company and A.O. Smith Corporation. AISI 200 and 300 series Austenitic stainless steels are divided into 300-series and 200-series subgroups. In 300 series stainless steels, the austenitic structure is obtained primarily by adding nickel. In 200 series stainless steels, the structure is obtained ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Tungsten
Tungsten (also called wolfram) is a chemical element; it has symbol W and atomic number 74. It is a metal found naturally on Earth almost exclusively in compounds with other elements. It was identified as a distinct element in 1781 and first isolated as a metal in 1783. Its important ores include scheelite and wolframite, the latter lending the element its alternative name. The free element is remarkable for its robustness, especially the fact that it has the highest melting point of all known elements, melting at . It also has the highest boiling point, at . Its density is 19.254 g/cm3, comparable with that of uranium and gold, and much higher (about 1.7 times) than that of lead. Polycrystalline tungsten is an intrinsically brittle and hard material (under standard conditions, when uncombined), making it difficult to work into metal. However, pure single-crystalline tungsten is more ductile and can be cut with a hard-steel hacksaw. Tungsten occurs in many alloys ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Phosphorus
Phosphorus is a chemical element; it has Chemical symbol, symbol P and atomic number 15. All elemental forms of phosphorus are highly Reactivity (chemistry), reactive and are therefore never found in nature. They can nevertheless be prepared artificially, the two most common allotropes being white phosphorus and red phosphorus. With as its only stable isotope, phosphorus has an occurrence in Earth's crust of about 0.1%, generally as phosphate rock. A member of the pnictogen family, phosphorus readily forms a wide variety of organic compound, organic and inorganic compound, inorganic compounds, with as its main oxidation states +5, +3 and −3. The isolation of white phosphorus in 1669 by Hennig Brand marked the scientific community's first discovery since Antiquity of an element. The name phosphorus is a reference to the Phosphorus (morning star), god of the Morning star in Greek mythology, inspired by the faint glow of white phosphorus when exposed to oxygen. This property is ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Silicon
Silicon is a chemical element; it has symbol Si and atomic number 14. It is a hard, brittle crystalline solid with a blue-grey metallic lustre, and is a tetravalent metalloid (sometimes considered a non-metal) and semiconductor. It is a member of group 14 in the periodic table: carbon is above it; and germanium, tin, lead, and flerovium are below it. It is relatively unreactive. Silicon is a significant element that is essential for several physiological and metabolic processes in plants. Silicon is widely regarded as the predominant semiconductor material due to its versatile applications in various electrical devices such as transistors, solar cells, integrated circuits, and others. These may be due to its significant band gap, expansive optical transmission range, extensive absorption spectrum, surface roughening, and effective anti-reflection coating. Because of its high chemical affinity for oxygen, it was not until 1823 that Jöns Jakob Berzelius was first able to p ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Potential Energy Surface
A potential energy surface (PES) or energy landscape describes the energy of a Physical system, system, especially a collection of atoms, in terms of certain Parameter, parameters, normally the positions of the atoms. The Surface (mathematics), surface might define the energy as a Function (mathematics), function of one or more coordinates; if there is only one coordinate, the surface is called a ''potential energy curve'' or energy profile. An example is the Morse/Long-range potential. It is helpful to use the analogy of a landscape: for a system with two Degrees of freedom (physics and chemistry), degrees of freedom (e.g. two bond lengths), the value of the energy (analogy: the height of the land) is a function of two bond lengths (analogy: the coordinates of the position on the ground). The PES concept finds application in fields such as physics, chemistry and biochemistry, especially in the theoretical sub-branches of these subjects. It can be used to theoretically explore p ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Learning
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of Computational statistics, statistical algorithms that can learn from data and generalise to unseen data, and thus perform Task (computing), tasks without explicit Machine code, instructions. Within a subdiscipline in machine learning, advances in the field of deep learning have allowed Neural network (machine learning), neural networks, a class of statistical algorithms, to surpass many previous machine learning approaches in performance. ML finds application in many fields, including natural language processing, computer vision, speech recognition, email filtering, agriculture, and medicine. The application of ML to business problems is known as predictive analytics. Statistics and mathematical optimisation (mathematical programming) methods comprise the foundations of machine learning. Data mining is a related field of study, focusing on exploratory data analysi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Convolution
In mathematics (in particular, functional analysis), convolution is a operation (mathematics), mathematical operation on two function (mathematics), functions f and g that produces a third function f*g, as the integral of the product of the two functions after one is reflected about the y-axis and shifted. The term ''convolution'' refers to both the resulting function and to the process of computing it. The integral is evaluated for all values of shift, producing the convolution function. The choice of which function is reflected and shifted before the integral does not change the integral result (see #Properties, commutativity). Graphically, it expresses how the 'shape' of one function is modified by the other. Some features of convolution are similar to cross-correlation: for real-valued functions, of a continuous or discrete variable, convolution f*g differs from cross-correlation f \star g only in that either f(x) or g(x) is reflected about the y-axis in convolution; thus i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Graph (discrete Mathematics)
In discrete mathematics, particularly in graph theory, a graph is a structure consisting of a Set (mathematics), set of objects where some pairs of the objects are in some sense "related". The objects are represented by abstractions called ''Vertex (graph theory), vertices'' (also called ''nodes'' or ''points'') and each of the related pairs of vertices is called an ''edge'' (also called ''link'' or ''line''). Typically, a graph is depicted in diagrammatic form as a set of dots or circles for the vertices, joined by lines or curves for the edges. The edges may be directed or undirected. For example, if the vertices represent people at a party, and there is an edge between two people if they shake hands, then this graph is undirected because any person ''A'' can shake hands with a person ''B'' only if ''B'' also shakes hands with ''A''. In contrast, if an edge from a person ''A'' to a person ''B'' means that ''A'' owes money to ''B'', then this graph is directed, because owing mon ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
