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The Fascinating World of Low-Dimensional Quantum Spin Systems: Ab Initio Modeling

In recent times, ab initio density functional theory has emerged as a powerful tool for making the connection between models and materials. Insulating transition metal oxides with a small spin forms a fascinating class of strongly correlated systems that exhibit spin-gap states, spin–charge separati...

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Autor principal: Saha-Dasgupta, Tanusri
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7998400/
https://www.ncbi.nlm.nih.gov/pubmed/33802160
http://dx.doi.org/10.3390/molecules26061522
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author Saha-Dasgupta, Tanusri
author_facet Saha-Dasgupta, Tanusri
author_sort Saha-Dasgupta, Tanusri
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description In recent times, ab initio density functional theory has emerged as a powerful tool for making the connection between models and materials. Insulating transition metal oxides with a small spin forms a fascinating class of strongly correlated systems that exhibit spin-gap states, spin–charge separation, quantum criticality, superconductivity, etc. The coupling between spin, charge, and orbital degrees of freedom makes the chemical insights equally important to the strong correlation effects. In this review, we establish the usefulness of ab initio tools within the framework of the N-th order muffin orbital (NMTO)-downfolding technique in the identification of a spin model of insulating oxides with small spins. The applicability of the method has been demonstrated by drawing on examples from a large number of cases from the cuprate, vanadate, and nickelate families. The method was found to be efficient in terms of the characterization of underlying spin models that account for the measured magnetic data and provide predictions for future experiments.
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spelling pubmed-79984002021-03-28 The Fascinating World of Low-Dimensional Quantum Spin Systems: Ab Initio Modeling Saha-Dasgupta, Tanusri Molecules Review In recent times, ab initio density functional theory has emerged as a powerful tool for making the connection between models and materials. Insulating transition metal oxides with a small spin forms a fascinating class of strongly correlated systems that exhibit spin-gap states, spin–charge separation, quantum criticality, superconductivity, etc. The coupling between spin, charge, and orbital degrees of freedom makes the chemical insights equally important to the strong correlation effects. In this review, we establish the usefulness of ab initio tools within the framework of the N-th order muffin orbital (NMTO)-downfolding technique in the identification of a spin model of insulating oxides with small spins. The applicability of the method has been demonstrated by drawing on examples from a large number of cases from the cuprate, vanadate, and nickelate families. The method was found to be efficient in terms of the characterization of underlying spin models that account for the measured magnetic data and provide predictions for future experiments. MDPI 2021-03-10 /pmc/articles/PMC7998400/ /pubmed/33802160 http://dx.doi.org/10.3390/molecules26061522 Text en © 2021 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Saha-Dasgupta, Tanusri
The Fascinating World of Low-Dimensional Quantum Spin Systems: Ab Initio Modeling
title The Fascinating World of Low-Dimensional Quantum Spin Systems: Ab Initio Modeling
title_full The Fascinating World of Low-Dimensional Quantum Spin Systems: Ab Initio Modeling
title_fullStr The Fascinating World of Low-Dimensional Quantum Spin Systems: Ab Initio Modeling
title_full_unstemmed The Fascinating World of Low-Dimensional Quantum Spin Systems: Ab Initio Modeling
title_short The Fascinating World of Low-Dimensional Quantum Spin Systems: Ab Initio Modeling
title_sort fascinating world of low-dimensional quantum spin systems: ab initio modeling
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7998400/
https://www.ncbi.nlm.nih.gov/pubmed/33802160
http://dx.doi.org/10.3390/molecules26061522
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