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Computational modelling of molecular nanomagnets

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Computational modelling of molecular nanomagnetsedited by Gopalan Rajaraman.
其他作者:	Rajaraman, Gopalan.
出版者:	Cham :Springer International Publishing :2023.
面頁冊數:	xii, 499 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Nanostructured materialsMagnetic properties
電子資源:	https://doi.org/10.1007/978-3-031-31038-6
ISBN:	9783031310386$q(electronic bk.)

Computational modelling of molecular nanomagnets
Computational modelling of molecular nanomagnets[electronic resource] /edited by Gopalan Rajaraman. - Cham :Springer International Publishing :2023. - xii, 499 p. :ill., digital ;24 cm. - Challenges and advances in computational chemistry and physics,v. 342542-4483 ;. - Challenges and advances in computational chemistry and physics ;v.11.

Ab initio investigation of anisotropic magnetism and magnetization blocking in metal complexes -- Analytical derivations for the description of magnetic anisotropy in transition metal complexes -- Calculations of Magnetic Exchange in Multinuclear Compounds -- Exact diagonalization techniques for quantum spin systems -- Modeling magnetic properties of actinide complexes -- Spin-Phonon Relaxation in Magnetic Molecules: Theory, Predictions and Insights -- Ab initio Modelling of Lanthanide Based Molecular Magnets: Where to from Here? -- Molecular Magnets on Surfaces: in silico recipes for a successful marriage -- Theoretical Approaches for Electron Transport through Magnetic Molecules.

This book summarizes the state-of-the-art advances in the area of computational modelling of molecule-based magnets. Nowadays, various computational tools based on DFT, ab initio methods and other techniques are gaining attention in molecular nanomagnets and are successfully used to solve several outstanding problems in this area. This contributed volume discusses the theoretical foundation of the modelling of molecular magnets, starting from fitting the experimental magnetic data of very large molecules to the theory of pseudo-spin Hamiltonian approach and spin-phonon relaxations mechanisms, while it also presents examples of contemporary applications of both transition metal and lanthanide molecular magnets. In addition, the transport characteristics of molecules when placed at an interface and how these assemble on surfaces are also reviewed. This book is a great tool for researchers working in the fields of molecular magnetism and computational/theoretical chemistry and will also benefit graduate students specializing in physical-inorganic chemistry and molecular modelling. Chapter 6 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

ISBN: 9783031310386$q(electronic bk.)

Standard No.: 10.1007/978-3-031-31038-6doiSubjects--Topical Terms:

956789
Nanostructured materials
--Magnetic properties

LC Class. No.: TA418.9.N35 / C66 2023

Dewey Class. No.: 620.115

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520 $a This book summarizes the state-of-the-art advances in the area of computational modelling of molecule-based magnets. Nowadays, various computational tools based on DFT, ab initio methods and other techniques are gaining attention in molecular nanomagnets and are successfully used to solve several outstanding problems in this area. This contributed volume discusses the theoretical foundation of the modelling of molecular magnets, starting from fitting the experimental magnetic data of very large molecules to the theory of pseudo-spin Hamiltonian approach and spin-phonon relaxations mechanisms, while it also presents examples of contemporary applications of both transition metal and lanthanide molecular magnets. In addition, the transport characteristics of molecules when placed at an interface and how these assemble on surfaces are also reviewed. This book is a great tool for researchers working in the fields of molecular magnetism and computational/theoretical chemistry and will also benefit graduate students specializing in physical-inorganic chemistry and molecular modelling. Chapter 6 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
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