NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
The electrochemical stability of room-temperature ionic liquids (RTILs) is a critical design consideration for electrochemical applications. An electrochemical solvent, such as the electrolyte in a lithium-ion battery or supercapacitor, must support the voltage in which the device operates. In this talk, we present the insights into the electrochemical stability of RTILs obtained using a novel combination of first principles density functional theory calculations and classical molecular dynamics simulations. We show that while simple gas phase models can be used to reveal broad qualitative trends in electrochemical stability, quantitative accuracy can be achieved only by explicitly modeling all inter-ion interactions in the liquid. Additionally, detailed investigations into the six room-temperature ionic liquids (ILs) formed from a combination of two common cations, 1-butyl-3-methylimidazolium (BMIM) and N ,N -propylmethylpyrrolidinium (P13), and three common anions, PF6 , BF4 , and bis(trifl uoromethylsulfonyl)imide (TFSI) provide surprising evidence of possible cation anodic instability, particularly in BMIM-based ILs.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
Branislav K. Nikoli
ć
Department of Physics and Astronomy, University of Delaware, U.S.A.
PHYS 624: Introduction to Solid State Physics
http://www.physics.udel.edu/~bnikolic/teaching/phys624/phys624.html
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
The electrochemical stability of room-temperature ionic liquids (RTILs) is a critical design consideration for electrochemical applications. An electrochemical solvent, such as the electrolyte in a lithium-ion battery or supercapacitor, must support the voltage in which the device operates. In this talk, we present the insights into the electrochemical stability of RTILs obtained using a novel combination of first principles density functional theory calculations and classical molecular dynamics simulations. We show that while simple gas phase models can be used to reveal broad qualitative trends in electrochemical stability, quantitative accuracy can be achieved only by explicitly modeling all inter-ion interactions in the liquid. Additionally, detailed investigations into the six room-temperature ionic liquids (ILs) formed from a combination of two common cations, 1-butyl-3-methylimidazolium (BMIM) and N ,N -propylmethylpyrrolidinium (P13), and three common anions, PF6 , BF4 , and bis(trifl uoromethylsulfonyl)imide (TFSI) provide surprising evidence of possible cation anodic instability, particularly in BMIM-based ILs.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
Branislav K. Nikoli
ć
Department of Physics and Astronomy, University of Delaware, U.S.A.
PHYS 624: Introduction to Solid State Physics
http://www.physics.udel.edu/~bnikolic/teaching/phys624/phys624.html
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
This is the plenary talk given by Prof Shyue Ping Ong at the 57th Sanibel Symposium held on St Simon's Island in Georgia, USA.
Abstract: Powered by methodological breakthroughs and computing advances, electronic structure methods have today become an indispensable toolkit in the materials designer’s arsenal. In this talk, I will discuss two emerging trends that holds the promise to continue to push the envelope in computational design of materials. The first trend is the development of robust software and data frameworks for the automatic generation, storage and analysis of materials data sets. The second is the advent of reliable central materials data repositories, such as the Materials Project, which provides the research community with efficient access to large quantities of property information that can be mined for trends or new materials. I will show how we have leveraged on these new tools to accelerate discovery and design in energy and structural materials as well as our efforts in contributing back to the community through further tool or data development. I will also provide my perspective on future challenges in high-throughput computational materials design.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
Federal Health IT capability; Predictive Modeling/Analytics for Fraud and Abuse Detection;COTS Product and RICE capability; Integration and Reporting Capability
This presentation was part of the workshop on Materials Project Software infrastructure conducted for the Materials Virtual Lab in Nov 10 2014. It presents an introduction to the Python Materials Genomics (pymatgen) materials analysis library. Pymatgen is a robust, open-source Python library for materials analysis. It currently powers the public Materials Project (http://www.materialsproject.org), an initiative to make calculated properties of all known inorganic materials available to materials researchers. These are some of the main features:
1. Highly flexible classes for the representation of Element, Site, Molecule, Structure objects.
Extensive io capabilities to manipulate many VASP (http://cms.mpi.univie.ac.at/vasp/) and ABINIT (http://www.abinit.org/) input and output files and the crystallographic information file format. This includes generating Structure objects from vasp input and output. There is also support for Gaussian input files and XYZ file for molecules.
2. Comprehensive tool to generate and view compositional and grand canonical phase diagrams.
3. Electronic structure analyses (DOS and Bandstructure).
4. Integration with the Materials Project REST API.
This presentation was part of the workshop on Materials Project Software infrastructure conducted for the Materials Virtual Lab in Nov 10 2014. It presents an introduction to the pymatgen-db database plugin for the pymatge) materials analysis library, and the custodian error recovery framework.
Pymatgen-db enables the creation of Materials Project-style MongoDB databases for management of materials data. A query engine is also provided to enable the easy translation of MongoDB docs to useful pymatgen objects for analysis purposes.
Custodian is a simple, robust and flexible just-in-time (JIT) job management framework written in Python. Using custodian, you can create wrappers that perform error checking, job management and error recovery. It has a simple plugin framework that allows you to develop specific job management workflows for different applications. Error recovery is an important aspect of many high-throughput projects that generate data on a large scale. The specific use case for custodian is for long running jobs, with potentially random errors. For example, there may be a script that takes several days to run on a server, with a 1% chance of some IO error causing the job to fail. Using custodian, one can develop a mechanism to gracefully recover from the error, and restart the job with modified parameters if necessary. The current version of Custodian also comes with sub-packages for error handling for Vienna Ab Initio Simulation Package (VASP) and QChem calculations.
At the end of this chapter you should be able to sketch the periodic table showing the groups and periods; identify the metals, metalloids and non-metals in the periodic table. Identify the representative elements, the transition elements, the transition metals, the lanthanides and actinides in the periodic table. Also, give the electron configuration of cations and anions; determine the trends in the physical properties of elements in a group; describe and explain the trends in atomic properties in the periodic table; compare the properties of families and elements; predict the properties of individual elements based on their position in the periodic table; and perform exercises and collaborative work with peers.
Lattice Energy LLC- Electroweak Neutron Production and Capture During Lightni...Lewis Larsen
Abstract. Electroweak production of low-energy neutrons in terrestrial lightning discharges was predicted by the Widom-Larsen theory of low energy nuclear reactions (LENRs) and recently confirmed by new Russian data. Contrary to longstanding belief, this data implies that neutron-capture-driven, non-stellar nucleosynthetic processes have likely been occurring in the environs of earth since it condensed as a planetary body ~4.5 billion years ago. Moreover, some researchers have recently suggested that lightning was significantly involved in dust processing during the era of the presolar nebula; if true, this would push non-stellar nucleosynthesis within the solar system even further back in time. Altogether, present thinking about types of nuclear processes affecting the chemical evolution of the earth and solar system may require revision.
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
We all have good and bad thoughts from time to time and situation to situation. We are bombarded daily with spiraling thoughts(both negative and positive) creating all-consuming feel , making us difficult to manage with associated suffering. Good thoughts are like our Mob Signal (Positive thought) amidst noise(negative thought) in the atmosphere. Negative thoughts like noise outweigh positive thoughts. These thoughts often create unwanted confusion, trouble, stress and frustration in our mind as well as chaos in our physical world. Negative thoughts are also known as “distorted thinking”.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Ethnobotany and Ethnopharmacology:
Ethnobotany in herbal drug evaluation,
Impact of Ethnobotany in traditional medicine,
New development in herbals,
Bio-prospecting tools for drug discovery,
Role of Ethnopharmacology in drug evaluation,
Reverse Pharmacology.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
3. Electronegativity
¡ Electronegativity, symbol χ, is a chemical property
that describes the tendency of an atom to attract
electrons (or electron density) towards itself.
¡ The electronegativity difference Δχ between two
atoms determine how likely one atom will rob the
other of electrons, and this in turn determines what
kind of bonds are formed between two atoms.
¡ Large Δχ è Ionic bonds
¡ Small Δχ è Covalent bonds
NANO 106 - Crystallography of Materials by Shyue Ping Ong - Lecture 7
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4. Measures of Electronegativity
¡ Pauling electronegativity
¡ Most commonly used definition based on valence bond theory
¡ Difference in A-B bond strength vs A-A and B-B bond strength
¡ Arbitrary reference is H, set at 2.20.
¡ Mulliken electronegativity
¡ Arithmetic mean of the first
ionization energy and the
electron affinity
¡ Also known as absolute
electronegativity
NANO 106 - Crystallography of Materials by Shyue Ping Ong - Lecture 7
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5. Ionic bonding
¡Bonding involving electrostatic attraction
between oppositely charge ions.
¡Non-directional, and geometry tends to follow
maximum packing rules. Often leads to much
higher coordination numbers.
¡Large Δχ
¡Example: LiF
¡ Pauling χLi = 1.0, χF = 3.98
¡ Li “donates” an electron to F to form Li+ and F-
¡ Both Li+ and F- have highly stable full octet
NANO 106 - Crystallography of Materials by Shyue Ping Ong - Lecture 7
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6. Covalent bonding
¡ Bonding that involves sharing of electron pairs
between atoms, typically to achieve stable full outer
shell
¡ Highly directional, with geometry determined by
Valence shell electron pair repulsion VSEPR rules
¡ Favored by small Δχ
¡ Example: H2 molecule
¡ The two H shares two electrons, forming a full He shell for each
H.
NANO 106 - Crystallography of Materials by Shyue Ping Ong - Lecture 7
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7. Other types of bonds
¡Metallic bonds
¡ Metals readily give up their weakly bound outer
electron(s) to become positive ions in a “sea” of
electrons.
¡ Valence electrons are not closely associated with any
particular atom, resulting in free motion and high
electrical conductivity.
¡Van Der Waals bonds
¡ Due to small instantaneous charge redistributions, which
cause an effective polarization of the molecule, i.e.
centers of gravity of positive and negative charges do
not coincide.
¡ Polarization result in effective attractive force.
NANO 106 - Crystallography of Materials by Shyue Ping Ong - Lecture 7
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8. Pauling’s rules
¡Five rules published by Linus Pauling in 1929
for determining the crystal structures of
complex ionic crystals.
¡Before we discuss these rules, it is important to
first establish the concept of atomic and ionic
radii.
NANO 106 - Crystallography of Materials by Shyue Ping Ong - Lecture 7
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9. Atomic and ionic radii
¡Size of an atom / ion depends on size of nucleus
and number of valence electrons
¡Atoms with larger number of electrons generally
have a larger size than atoms with smaller
number of electrons
¡Size of ions ≠ Size of atoms as ions have gained or
lost electrons
¡ As charge on ion increases, there will be less electrons
and the ion will have a smaller radius.
¡ As the atomic number increases in any given column of
the Periodic Table, the number of protons and electrons
increases and thus the size of the atom or ion increases.
NANO 106 - Crystallography of Materials by Shyue Ping Ong - Lecture 7
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10. Determination of Ionic Radii
¡X-ray crystallography (final third of course)
can provide distances between ions.
¡However, this does not tell us where the
boundary between ions are, and hence does
not provide information on ionic radii.
¡One trick is therefore to choose ions that are
extremely different in size, e.g. Li+ and I-. In LiI,
the Li+ are effectively in the interstitial sites
with the I- touching each other, allowing one
to determine the radii of I-
NANO 106 - Crystallography of Materials by Shyue Ping Ong - Lecture 7
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11. Trends in Ionic Radii
NANO 106 - Crystallography of Materials by Shyue Ping Ong - Lecture 7
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12. Pauling’s First Rule
¡ A coordinated polyhedron of anions is formed about
each cation, the cation-anion distance determined
by the sum of ionic radii and the coordination
number by the radius ratio.
¡ Derived purely from geometric considerations of
sphere packing
NANO 106 - Crystallography of Materials by Shyue Ping Ong - Lecture 7
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Applying Pythagoras’
theorem, we get Rx/Rz
= 0.732
13. Coordination and radius ratios
NANO 106 - Crystallography of Materials by Shyue Ping Ong - Lecture 7
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Radius ratio C.N. polyhedron
0.225 4 tetrahedron
0.414 6 octahedron
0.592 7 capped octahedron
0.645 8 square antiprism (anticube)
0.732 8 cube
0.732 9 triaugmented triangular prism
1 12 cuboctahedron
14. Pauling’s Second Rule: The
electrostatic valence rule
¡ An ionic structure will be stable to the extent that the
sum of the strengths of the electrostatic bonds that
reach an anion equal the charge on that anion, i.e.,
a stable ionic structure must be arranged to preserve
local electroneutrality.
¡ Electrostatic valency is defined as charge on ion /
coordination number
where εis the charge of the anion and the summation
is over the adjacent cations.
NANO 106 - Crystallography of Materials by Shyue Ping Ong - Lecture 7
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ε = si
i
∑
15. Pauling’s Third Rule
¡ The sharing of edges and particularly faces by two anion
polyhedra decreases the stability of an ionic structure.
Sharing of corners does not decrease stability as much, so
(for example) octahedra may share corners with one
another.
¡ Effect is largest for cations with high charge and low C.N.
(especially when r+/r- approaches the lower limit of the
polyhedral stability).
¡ Vertex-sharing between tetrahedra or octahedra is energetically
stable
¡ Edge-sharing between polyhedra is less stable; rare for
tetrahedra, more common for octahedra
¡ Face-sharing (2 cations share 3 anions) between polyhedra is
unstable; never occurs for tetrahedra; rare for octahedra
NANO 106 - Crystallography of Materials by Shyue Ping Ong - Lecture 7
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16. Pauling’s Fourth Rule
¡In a crystal containing different cations, those
of high valency and small coordination
number tend not to share polyhedron
elements with one another.
NANO 106 - Crystallography of Materials by Shyue Ping Ong - Lecture 7
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17. Pauling’s Fifth Rule: The rule of
parsimony
¡ The number of essentially different kinds of
constituents in a crystal tends to be small. The
repeating units will tend to be identical because
each atom in the structure is most stable in a specific
environment. There may be two or three types of
polyhedra, such as tetrahedra or octahedra, but
there will not be many different types.
NANO 106 - Crystallography of Materials by Shyue Ping Ong - Lecture 7
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