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8.044 Statistical Physics I (MIT) 8.044 Statistical Physics I (MIT)

Description

This course offers an introduction to probability, statistical mechanics, and thermodynamics. Numerous examples are used to illustrate a wide variety of physical phenomena such as magnetism, polyatomic gases, thermal radiation, electrons in solids, and noise in electronic devices. This course offers an introduction to probability, statistical mechanics, and thermodynamics. Numerous examples are used to illustrate a wide variety of physical phenomena such as magnetism, polyatomic gases, thermal radiation, electrons in solids, and noise in electronic devices.Subjects

probability | probability | statistical mechanics | statistical mechanics | thermodynamics | thermodynamics | random variables | random variables | joint and conditional probability densities | joint and conditional probability densities | functions of a random variable | functions of a random variable | macroscopic variables | macroscopic variables | thermodynamic equilibrium | thermodynamic equilibrium | fundamental assumption of statistical mechanics | fundamental assumption of statistical mechanics | microcanonical and canonical ensembles | microcanonical and canonical ensembles | First | First | second | second | and third laws of thermodynamics | and third laws of thermodynamics | magnetism | magnetism | polyatomic gases | polyatomic gases | hermal radiation | hermal radiation | thermal radiation | thermal radiation | electrons in solids | electrons in solids | and noise in electronic devices | and noise in electronic devices | First | second | and third laws of thermodynamics | First | second | and third laws of thermodynamicsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata8.044 Statistical Physics I (MIT) 8.044 Statistical Physics I (MIT)

Description

Introduction to probability, statistical mechanics, and thermodynamics. Random variables, joint and conditional probability densities, and functions of a random variable. Concepts of macroscopic variables and thermodynamic equilibrium, fundamental assumption of statistical mechanics, microcanonical and canonical ensembles. First, second, and third laws of thermodynamics. Numerous examples illustrating a wide variety of physical phenomena such as magnetism, polyatomic gases, thermal radiation, electrons in solids, and noise in electronic devices. Concurrent enrollment in 8.04, Quantum Physics I, is recommended. Introduction to probability, statistical mechanics, and thermodynamics. Random variables, joint and conditional probability densities, and functions of a random variable. Concepts of macroscopic variables and thermodynamic equilibrium, fundamental assumption of statistical mechanics, microcanonical and canonical ensembles. First, second, and third laws of thermodynamics. Numerous examples illustrating a wide variety of physical phenomena such as magnetism, polyatomic gases, thermal radiation, electrons in solids, and noise in electronic devices. Concurrent enrollment in 8.04, Quantum Physics I, is recommended.Subjects

probability | probability | statistical mechanics | statistical mechanics | thermodynamics | thermodynamics | random variables | random variables | joint and conditional probability densities | joint and conditional probability densities | functions of a random variable | functions of a random variable | macroscopic variables | macroscopic variables | thermodynamic equilibrium | thermodynamic equilibrium | fundamental assumption of statistical mechanics | fundamental assumption of statistical mechanics | microcanonical and canonical ensembles | microcanonical and canonical ensembles | First | First | second | second | and third laws of thermodynamics | and third laws of thermodynamics | magnetism | magnetism | polyatomic gases | polyatomic gases | hermal radiation | hermal radiation | thermal radiation | thermal radiation | electrons in solids | electrons in solids | and noise in electronic devices | and noise in electronic devices | First | second | and third laws of thermodynamics | First | second | and third laws of thermodynamicsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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Theory and application of atomistic computer simulations to model, understand, and predict the properties of real materials. Energy models, from classical potentials to first-principles approaches. Density-functional theory and the total-energy pseudopotential method. Errors and accuracy of quantitative predictions. Thermodynamic ensembles, Monte Carlo sampling and molecular dynamics simulations. Free energies and phase transitions. Fluctuations and transport properties. Coarse-graining approaches and mesoscale models. Theory and application of atomistic computer simulations to model, understand, and predict the properties of real materials. Energy models, from classical potentials to first-principles approaches. Density-functional theory and the total-energy pseudopotential method. Errors and accuracy of quantitative predictions. Thermodynamic ensembles, Monte Carlo sampling and molecular dynamics simulations. Free energies and phase transitions. Fluctuations and transport properties. Coarse-graining approaches and mesoscale models.Subjects

atomistic computer simulations | atomistic computer simulations | Density-functional theory | Density-functional theory | total-energy pseudopotential method | total-energy pseudopotential method | Thermodynamic ensembles | Thermodynamic ensembles | Monte Carlo sampling | Monte Carlo sampling | molecular dynamics simulations | molecular dynamics simulations | Free energies | Free energies | phase transitions | phase transitions | Coarse-graining approaches | Coarse-graining approaches | mesoscale models | mesoscale modelsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata9.322J Genetic Neurobiology (MIT) 9.322J Genetic Neurobiology (MIT)

Description

This course deals with the specific functions of neurons, the interactions of neurons in development, and the organization of neuronal ensembles to produce behavior. Topics covered include the analysis of mutations, and molecular analysis of the genes required for nervous system function. In particular, this course focuses on research work done with nematodes, fruit flies, mice, and humans. This course deals with the specific functions of neurons, the interactions of neurons in development, and the organization of neuronal ensembles to produce behavior. Topics covered include the analysis of mutations, and molecular analysis of the genes required for nervous system function. In particular, this course focuses on research work done with nematodes, fruit flies, mice, and humans.Subjects

neurobiology | neurobiology | genetics | genetics | bacterial chemoreception | bacterial chemoreception | neurogenomics | neurogenomics | genetic analysis | genetic analysis | axonal pathfinding | axonal pathfinding | neurodevelopment | neurodevelopment | synapse formation | synapse formation | neurogenetics | neurogenetics | higher brain function | higher brain function | neuronal ensembles | neuronal ensembles | molecular analysis | molecular analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadataDescription

This course uses the theory and application of atomistic computer simulations to model, understand, and predict the properties of real materials. Specific topics include: energy models from classical potentials to first-principles approaches; density functional theory and the total-energy pseudopotential method; errors and accuracy of quantitative predictions: thermodynamic ensembles, Monte Carlo sampling and molecular dynamics simulations; free energy and phase transitions; fluctuations and transport properties; and coarse-graining approaches and mesoscale models. The course employs case studies from industrial applications of advanced materials to nanotechnology. Several laboratories will give students direct experience with simulations of classical force fields, electronic-structure app This course uses the theory and application of atomistic computer simulations to model, understand, and predict the properties of real materials. Specific topics include: energy models from classical potentials to first-principles approaches; density functional theory and the total-energy pseudopotential method; errors and accuracy of quantitative predictions: thermodynamic ensembles, Monte Carlo sampling and molecular dynamics simulations; free energy and phase transitions; fluctuations and transport properties; and coarse-graining approaches and mesoscale models. The course employs case studies from industrial applications of advanced materials to nanotechnology. Several laboratories will give students direct experience with simulations of classical force fields, electronic-structure appSubjects

simulation | simulation | computer simulation | computer simulation | atomistic computer simulations | atomistic computer simulations | Density-functional theory | Density-functional theory | DFT | DFT | Hartree-Fock | Hartree-Fock | total-energy pseudopotential | total-energy pseudopotential | thermodynamics | thermodynamics | thermodynamic ensembles | thermodynamic ensembles | quantum mechanics | quantum mechanics | first-principles | first-principles | Monte Carlo sampling | Monte Carlo sampling | molecular dynamics | molecular dynamics | finite temperature | finite temperature | Free energies | Free energies | phase transitions | phase transitions | Coarse-graining | Coarse-graining | mesoscale model | mesoscale model | nanotube | nanotube | alloy | alloyLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata9.322J Genetic Neurobiology (MIT) 9.322J Genetic Neurobiology (MIT)

Description

This course deals with the specific functions of neurons, the interactions of neurons in development, and the organization of neuronal ensembles to produce behavior. Topics covered include the analysis of mutations, and molecular analysis of the genes required for nervous system function. In particular, this course focuses on research work done with nematodes, fruit flies, mice, and humans. This course deals with the specific functions of neurons, the interactions of neurons in development, and the organization of neuronal ensembles to produce behavior. Topics covered include the analysis of mutations, and molecular analysis of the genes required for nervous system function. In particular, this course focuses on research work done with nematodes, fruit flies, mice, and humans.Subjects

neurobiology | neurobiology | genetics | genetics | bacterial chemoreception | bacterial chemoreception | neurogenomics | neurogenomics | genetic analysis | genetic analysis | axonal pathfinding | axonal pathfinding | neurodevelopment | neurodevelopment | synapse formation | synapse formation | neurogenetics | neurogenetics | higher brain function | higher brain function | neuronal ensembles | neuronal ensembles | molecular analysis | molecular analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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This course is an introduction to the basics of random matrix theory, motivated by engineering and scientific applications. This course is an introduction to the basics of random matrix theory, motivated by engineering and scientific applications.Subjects

Random matrix theory | Random matrix theory | Matrix Jacobians | Matrix Jacobians | Wishart Matrices | Wishart Matrices | Wigner's Semi-Circular laws | Wigner's Semi-Circular laws | Matrix beta ensembles | Matrix beta ensembles | free probability | free probability | spherical coordinates | spherical coordinates | wedging | wedging | Plucker coordinates | Plucker coordinates | matrix factorizations | matrix factorizations | householder transformations | householder transformations | Stiefel manifold | Stiefel manifold | Cauchey-Binet theorem | Cauchey-Binet theorem | Telatar's paper | Telatar's paper | level densities | level densities | orthogonal polynomials | orthogonal polynomials | matrix integrals | matrix integrals | hypergeometric functions | hypergeometric functions | wireless communictions | wireless communictions | eigenvalue density | eigenvalue density | sample covariance matrices | sample covariance matrices | Marcenko-Pastur theorem | Marcenko-Pastur theorem | wireless communications | wireless communicationsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata3.20 Materials at Equilibrium (SMA 5111) (MIT) 3.20 Materials at Equilibrium (SMA 5111) (MIT)

Description

Material covered in this course includes the following topics: Laws of thermodynamics: general formulation and applications to mechanical, electromagnetic and electrochemical systems, solutions, and phase diagrams Computation of phase diagrams Statistical thermodynamics and relation between microscopic and macroscopic properties, including ensembles, gases, crystal lattices, phase transitions Applications to phase stability and properties of mixtures Computational modeling Interfaces This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5111 (Materials at Equilibrium). Material covered in this course includes the following topics: Laws of thermodynamics: general formulation and applications to mechanical, electromagnetic and electrochemical systems, solutions, and phase diagrams Computation of phase diagrams Statistical thermodynamics and relation between microscopic and macroscopic properties, including ensembles, gases, crystal lattices, phase transitions Applications to phase stability and properties of mixtures Computational modeling Interfaces This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5111 (Materials at Equilibrium).Subjects

thermodynamics | thermodynamics | mechanical | mechanical | electromagnetic and electrochemical systems | electromagnetic and electrochemical systems | phase diagrams | phase diagrams | Statistical thermodynamics | Statistical thermodynamics | microscopic and macroscopic properties | microscopic and macroscopic properties | ensembles | ensembles | gases | gases | crystal lattices | crystal lattices | phase transitions | phase transitions | phase stability | phase stability | properties of mixtures | properties of mixtures | Computational modeling | Computational modeling | Interfaces | Interfaces | mechanical | electromagnetic and electrochemical systems | mechanical | electromagnetic and electrochemical systems | Computational modeling; Interfaces | Computational modeling; Interfaces | mechanical systems | mechanical systems | electromagnetic systems | electromagnetic systems | electrochemical systems | electrochemical systems | laws of thermodynamics | laws of thermodynamics | solutions | solutions | microscopic properties | microscopic properties | macroscopic properties | macroscopic propertiesLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata8.044 Statistical Physics I (MIT) 8.044 Statistical Physics I (MIT)

Description

This course offers an introduction to probability, statistical mechanics, and thermodynamics. Numerous examples are used to illustrate a wide variety of physical phenomena such as magnetism, polyatomic gases, thermal radiation, electrons in solids, and noise in electronic devices.This course is an elective subject in MIT’s undergraduate Energy Studies Minor. This Institute-wide program complements the deep expertise obtained in any major with a broad understanding of the interlinked realms of science, technology, and social sciences as they relate to energy and associated environmental challenges. This course offers an introduction to probability, statistical mechanics, and thermodynamics. Numerous examples are used to illustrate a wide variety of physical phenomena such as magnetism, polyatomic gases, thermal radiation, electrons in solids, and noise in electronic devices.This course is an elective subject in MIT’s undergraduate Energy Studies Minor. This Institute-wide program complements the deep expertise obtained in any major with a broad understanding of the interlinked realms of science, technology, and social sciences as they relate to energy and associated environmental challenges.Subjects

probability | probability | statistical mechanics | statistical mechanics | thermodynamics | thermodynamics | random variables | random variables | joint and conditional probability densities | joint and conditional probability densities | functions of a random variable | functions of a random variable | macroscopic variables | macroscopic variables | thermodynamic equilibrium | thermodynamic equilibrium | fundamental assumption of statistical mechanics | fundamental assumption of statistical mechanics | microcanonical and canonical ensembles | microcanonical and canonical ensembles | First | second | and third laws of thermodynamics | First | second | and third laws of thermodynamics | magnetism | magnetism | polyatomic gases | polyatomic gases | thermal radiation | thermal radiation | electrons in solids | electrons in solids | noise in electronic devices | noise in electronic devicesLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata8.044 Statistical Physics I (MIT) 8.044 Statistical Physics I (MIT)

Description

This course offers an introduction to probability, statistical mechanics, and thermodynamics. Numerous examples are used to illustrate a wide variety of physical phenomena such as magnetism, polyatomic gases, thermal radiation, electrons in solids, and noise in electronic devices. This course offers an introduction to probability, statistical mechanics, and thermodynamics. Numerous examples are used to illustrate a wide variety of physical phenomena such as magnetism, polyatomic gases, thermal radiation, electrons in solids, and noise in electronic devices.Subjects

probability | probability | statistical mechanics | statistical mechanics | thermodynamics | thermodynamics | random variables | random variables | joint and conditional probability densities | joint and conditional probability densities | functions of a random variable | functions of a random variable | macroscopic variables | macroscopic variables | thermodynamic equilibrium | thermodynamic equilibrium | fundamental assumption of statistical mechanics | fundamental assumption of statistical mechanics | microcanonical and canonical ensembles | microcanonical and canonical ensembles | First | First | second | second | and third laws of thermodynamics | and third laws of thermodynamics | magnetism | magnetism | polyatomic gases | polyatomic gases | hermal radiation | hermal radiation | thermal radiation | thermal radiation | electrons in solids | electrons in solids | and noise in electronic devices | and noise in electronic devices | First | second | and third laws of thermodynamics | First | second | and third laws of thermodynamicsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata8.044 Statistical Physics I (MIT)

Description

Introduction to probability, statistical mechanics, and thermodynamics. Random variables, joint and conditional probability densities, and functions of a random variable. Concepts of macroscopic variables and thermodynamic equilibrium, fundamental assumption of statistical mechanics, microcanonical and canonical ensembles. First, second, and third laws of thermodynamics. Numerous examples illustrating a wide variety of physical phenomena such as magnetism, polyatomic gases, thermal radiation, electrons in solids, and noise in electronic devices. Concurrent enrollment in 8.04, Quantum Physics I, is recommended.Subjects

probability | statistical mechanics | thermodynamics | random variables | joint and conditional probability densities | functions of a random variable | macroscopic variables | thermodynamic equilibrium | fundamental assumption of statistical mechanics | microcanonical and canonical ensembles | First | second | and third laws of thermodynamics | magnetism | polyatomic gases | hermal radiation | thermal radiation | electrons in solids | and noise in electronic devices | First | second | and third laws of thermodynamicsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata8.044 Statistical Physics I (MIT)

Description

This course offers an introduction to probability, statistical mechanics, and thermodynamics. Numerous examples are used to illustrate a wide variety of physical phenomena such as magnetism, polyatomic gases, thermal radiation, electrons in solids, and noise in electronic devices.Subjects

probability | statistical mechanics | thermodynamics | random variables | joint and conditional probability densities | functions of a random variable | macroscopic variables | thermodynamic equilibrium | fundamental assumption of statistical mechanics | microcanonical and canonical ensembles | First | second | and third laws of thermodynamics | magnetism | polyatomic gases | hermal radiation | thermal radiation | electrons in solids | and noise in electronic devices | First | second | and third laws of thermodynamicsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadataDescription

Subjects

wales | children | cymru | festivals | jazz | bands | musicalinstruments | llyfrgellgenedlaetholcymru | nationallibraryofwales | sociallife | filmnegatives | blaencwm | musicensembles | charlesgeoff19092002 | negyddffilmLicense

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See all metadata3.20 Materials at Equilibrium (SMA 5111) (MIT)

Description

Material covered in this course includes the following topics: Laws of thermodynamics: general formulation and applications to mechanical, electromagnetic and electrochemical systems, solutions, and phase diagrams Computation of phase diagrams Statistical thermodynamics and relation between microscopic and macroscopic properties, including ensembles, gases, crystal lattices, phase transitions Applications to phase stability and properties of mixtures Computational modeling Interfaces This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5111 (Materials at Equilibrium).Subjects

thermodynamics | mechanical | electromagnetic and electrochemical systems | phase diagrams | Statistical thermodynamics | microscopic and macroscopic properties | ensembles | gases | crystal lattices | phase transitions | phase stability | properties of mixtures | Computational modeling | Interfaces | mechanical | electromagnetic and electrochemical systems | Computational modeling; Interfaces | mechanical systems | electromagnetic systems | electrochemical systems | laws of thermodynamics | solutions | microscopic properties | macroscopic propertiesLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata9.322J Genetic Neurobiology (MIT)

Description

This course deals with the specific functions of neurons, the interactions of neurons in development, and the organization of neuronal ensembles to produce behavior. Topics covered include the analysis of mutations, and molecular analysis of the genes required for nervous system function. In particular, this course focuses on research work done with nematodes, fruit flies, mice, and humans.Subjects

neurobiology | genetics | bacterial chemoreception | neurogenomics | genetic analysis | axonal pathfinding | neurodevelopment | synapse formation | neurogenetics | higher brain function | neuronal ensembles | molecular analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata18.996 Random Matrix Theory and Its Applications (MIT)

Description

This course is an introduction to the basics of random matrix theory, motivated by engineering and scientific applications.Subjects

Random matrix theory | Matrix Jacobians | Wishart Matrices | Wigner's Semi-Circular laws | Matrix beta ensembles | free probability | spherical coordinates | wedging | Plucker coordinates | matrix factorizations | householder transformations | Stiefel manifold | Cauchey-Binet theorem | Telatar's paper | level densities | orthogonal polynomials | matrix integrals | hypergeometric functions | wireless communictions | eigenvalue density | sample covariance matrices | Marcenko-Pastur theorem | wireless communicationsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata3.20 Materials at Equilibrium (SMA 5111) (MIT)

Description

Material covered in this course includes the following topics: Laws of thermodynamics: general formulation and applications to mechanical, electromagnetic and electrochemical systems, solutions, and phase diagrams Computation of phase diagrams Statistical thermodynamics and relation between microscopic and macroscopic properties, including ensembles, gases, crystal lattices, phase transitions Applications to phase stability and properties of mixtures Computational modeling Interfaces This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5111 (Materials at Equilibrium).Subjects

thermodynamics | mechanical | electromagnetic and electrochemical systems | phase diagrams | Statistical thermodynamics | microscopic and macroscopic properties | ensembles | gases | crystal lattices | phase transitions | phase stability | properties of mixtures | Computational modeling | Interfaces | mechanical | electromagnetic and electrochemical systems | Computational modeling; Interfaces | mechanical systems | electromagnetic systems | electrochemical systems | laws of thermodynamics | solutions | microscopic properties | macroscopic propertiesLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadataGrand Funeral Procession in Memory of General Jackson

Description

Subjects

cornelluniversitylibrary | popularprints | jacksonandrew | funerals | processions | horses | bandsensembles | urns | uniforms | newyorknewyork | soldiers | firemen | independentorderofoddfellows | americanflags | commemoratives | culidentifier:value=2214pr0039 | culidentifier:lunafield=idnumberLicense

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Cornell University Library | FlickRAttribution

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See all metadata3.320 Atomistic Computer Modeling of Materials (SMA 5107) (MIT)

Description

This course uses the theory and application of atomistic computer simulations to model, understand, and predict the properties of real materials. Specific topics include: energy models from classical potentials to first-principles approaches; density functional theory and the total-energy pseudopotential method; errors and accuracy of quantitative predictions: thermodynamic ensembles, Monte Carlo sampling and molecular dynamics simulations; free energy and phase transitions; fluctuations and transport properties; and coarse-graining approaches and mesoscale models. The course employs case studies from industrial applications of advanced materials to nanotechnology. Several laboratories will give students direct experience with simulations of classical force fields, electronic-structure appSubjects

simulation | computer simulation | atomistic computer simulations | Density-functional theory | DFT | Hartree-Fock | total-energy pseudopotential | thermodynamics | thermodynamic ensembles | quantum mechanics | first-principles | Monte Carlo sampling | molecular dynamics | finite temperature | Free energies | phase transitions | Coarse-graining | mesoscale model | nanotube | alloyLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata3.320 Atomistic Computer Modeling of Materials (MIT)

Description

Theory and application of atomistic computer simulations to model, understand, and predict the properties of real materials. Energy models, from classical potentials to first-principles approaches. Density-functional theory and the total-energy pseudopotential method. Errors and accuracy of quantitative predictions. Thermodynamic ensembles, Monte Carlo sampling and molecular dynamics simulations. Free energies and phase transitions. Fluctuations and transport properties. Coarse-graining approaches and mesoscale models.Subjects

atomistic computer simulations | Density-functional theory | total-energy pseudopotential method | Thermodynamic ensembles | Monte Carlo sampling | molecular dynamics simulations | Free energies | phase transitions | Coarse-graining approaches | mesoscale modelsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata8.044 Statistical Physics I (MIT)

Description

This course offers an introduction to probability, statistical mechanics, and thermodynamics. Numerous examples are used to illustrate a wide variety of physical phenomena such as magnetism, polyatomic gases, thermal radiation, electrons in solids, and noise in electronic devices.This course is an elective subject in MIT’s undergraduate Energy Studies Minor. This Institute-wide program complements the deep expertise obtained in any major with a broad understanding of the interlinked realms of science, technology, and social sciences as they relate to energy and associated environmental challenges.Subjects

probability | statistical mechanics | thermodynamics | random variables | joint and conditional probability densities | functions of a random variable | macroscopic variables | thermodynamic equilibrium | fundamental assumption of statistical mechanics | microcanonical and canonical ensembles | First | second | and third laws of thermodynamics | magnetism | polyatomic gases | thermal radiation | electrons in solids | noise in electronic devicesLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata8.044 Statistical Physics I (MIT)

Description

This course offers an introduction to probability, statistical mechanics, and thermodynamics. Numerous examples are used to illustrate a wide variety of physical phenomena such as magnetism, polyatomic gases, thermal radiation, electrons in solids, and noise in electronic devices.Subjects

probability | statistical mechanics | thermodynamics | random variables | joint and conditional probability densities | functions of a random variable | macroscopic variables | thermodynamic equilibrium | fundamental assumption of statistical mechanics | microcanonical and canonical ensembles | First | second | and third laws of thermodynamics | magnetism | polyatomic gases | hermal radiation | thermal radiation | electrons in solids | and noise in electronic devices | First | second | and third laws of thermodynamicsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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Subjects

music | newyorkpubliclibrary | bands | photographs | 1900s | youngmen | xmlns:dc=httppurlorgdcelements11 | musicensembles | dc:identifier=httpdigitalgallerynyplorgnypldigitalid832187License

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See all metadata[Music ensemble with piano and bowed stringed instruments.]

Description

Subjects

music | woman | men | musicians | newyorkpubliclibrary | photographs | pianos | 1900s | xmlns:dc=httppurlorgdcelements11 | musicensembles | dc:identifier=httpdigitalgallerynyplorgnypldigitalid832191 | bowedstringedinstrumentsLicense

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See all metadata9.322J Genetic Neurobiology (MIT)

Description

This course deals with the specific functions of neurons, the interactions of neurons in development, and the organization of neuronal ensembles to produce behavior. Topics covered include the analysis of mutations, and molecular analysis of the genes required for nervous system function. In particular, this course focuses on research work done with nematodes, fruit flies, mice, and humans.Subjects

neurobiology | genetics | bacterial chemoreception | neurogenomics | genetic analysis | axonal pathfinding | neurodevelopment | synapse formation | neurogenetics | higher brain function | neuronal ensembles | molecular analysisLicense

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