{"title":"从组成电导率计算矿物集料电导率的综述","authors":"Kui Han , Simon Martin Clark","doi":"10.1016/j.sesci.2021.02.003","DOIUrl":null,"url":null,"abstract":"<div><p>The electrical conductivity of mineral aggregates depends both on the properties of the constitutive minerals and the ways those minerals are assembled. Mixing, or average models combine the conductivity of single phases to give bulk conductivity of rocks, thereby linking experimental measurements to geophysical observations. In order to compare these mixing models and allow an informed choice, several popular approaches, including bounds and average models, have been used to estimate the conductivity of a typical dry upper mantle and transition zone with a pyrolite composition. All the estimations calculated using the various average models lie between the rigorous constraint that is given by the HS bounds. The average models in this study are found to give similar bulk conductivities with the difference of less than 0.5 orders of magnitude, except the geometric mean, implying that the choice of the average models is insignificant. The effective electrical conductivity of pyrolite mantle has been derived from the conductivity of dry mantle minerals using the effective medium theory, and was found consistent with observed conductivity values for some subsurface regions of the Earth which we expect to be relatively dry. This provides us with baseline conductivity for a dry mantle, which is helpful to understand the water distribution in the deep earth.</p></div>","PeriodicalId":54172,"journal":{"name":"Solid Earth Sciences","volume":"6 2","pages":"Pages 111-128"},"PeriodicalIF":2.0000,"publicationDate":"2021-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.sesci.2021.02.003","citationCount":"4","resultStr":"{\"title\":\"Review of calculating the electrical conductivity of mineral aggregates from constituent conductivities\",\"authors\":\"Kui Han , Simon Martin Clark\",\"doi\":\"10.1016/j.sesci.2021.02.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The electrical conductivity of mineral aggregates depends both on the properties of the constitutive minerals and the ways those minerals are assembled. Mixing, or average models combine the conductivity of single phases to give bulk conductivity of rocks, thereby linking experimental measurements to geophysical observations. In order to compare these mixing models and allow an informed choice, several popular approaches, including bounds and average models, have been used to estimate the conductivity of a typical dry upper mantle and transition zone with a pyrolite composition. All the estimations calculated using the various average models lie between the rigorous constraint that is given by the HS bounds. The average models in this study are found to give similar bulk conductivities with the difference of less than 0.5 orders of magnitude, except the geometric mean, implying that the choice of the average models is insignificant. The effective electrical conductivity of pyrolite mantle has been derived from the conductivity of dry mantle minerals using the effective medium theory, and was found consistent with observed conductivity values for some subsurface regions of the Earth which we expect to be relatively dry. This provides us with baseline conductivity for a dry mantle, which is helpful to understand the water distribution in the deep earth.</p></div>\",\"PeriodicalId\":54172,\"journal\":{\"name\":\"Solid Earth Sciences\",\"volume\":\"6 2\",\"pages\":\"Pages 111-128\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2021-06-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.sesci.2021.02.003\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Solid Earth Sciences\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2451912X21000064\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Solid Earth Sciences","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2451912X21000064","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
Review of calculating the electrical conductivity of mineral aggregates from constituent conductivities
The electrical conductivity of mineral aggregates depends both on the properties of the constitutive minerals and the ways those minerals are assembled. Mixing, or average models combine the conductivity of single phases to give bulk conductivity of rocks, thereby linking experimental measurements to geophysical observations. In order to compare these mixing models and allow an informed choice, several popular approaches, including bounds and average models, have been used to estimate the conductivity of a typical dry upper mantle and transition zone with a pyrolite composition. All the estimations calculated using the various average models lie between the rigorous constraint that is given by the HS bounds. The average models in this study are found to give similar bulk conductivities with the difference of less than 0.5 orders of magnitude, except the geometric mean, implying that the choice of the average models is insignificant. The effective electrical conductivity of pyrolite mantle has been derived from the conductivity of dry mantle minerals using the effective medium theory, and was found consistent with observed conductivity values for some subsurface regions of the Earth which we expect to be relatively dry. This provides us with baseline conductivity for a dry mantle, which is helpful to understand the water distribution in the deep earth.