The Experts below are selected from a list of 15867 Experts worldwide ranked by ideXlab platform
Chris J. Pickard - One of the best experts on this subject based on the ideXlab platform.
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Revisiting metal fluorides as lithium-ion battery cathodes
Nature Materials, 2021Co-Authors: Xiao Hua, Alexander S. Eggeman, Elizabeth Castillo-martínez, Rosa Robert, Harry S. Geddes, Chris J. Pickard, Wei Meng, Kamila M. Wiaderek, Nathalie Pereira, Glenn G. AmatucciAbstract:Metal fluorides, promising lithium-ion battery cathode materials, have been classified as conversion materials due to the reconstructive phase transitions widely presumed to occur upon lithiation. We challenge this view by studying FeF_3 using X-ray total scattering and electron diffraction techniques that measure structure over multiple length scales coupled with density functional theory calculations, and by revisiting prior experimental studies of FeF_2 and CuF_2. Metal fluoride lithiation is instead dominated by diffusion-controlled displacement mechanisms, and a clear Topological Relationship between the metal fluoride F^− sublattices and that of LiF is established. Initial lithiation of FeF_3 forms FeF_2 on the particle’s surface, along with a cation-ordered and stacking-disordered phase, A-Li_ x Fe_ y F_3, which is structurally related to α-/β-LiMn^2+Fe^3+F_6 and which topotactically transforms to B- and then C-Li_ x Fe_ y F_3, before forming LiF and Fe. Lithiation of FeF_2 and CuF_2 results in a buffer phase between FeF_2/CuF_2 and LiF. The resulting principles will aid future developments of a wider range of isomorphic metal fluorides. Metal-fluoride-based lithium-ion battery cathodes are typically classified as conversion materials because reconstructive phase transitions are presumed to occur upon lithiation. Metal fluoride lithiation is now shown to be dominated instead by diffusion-controlled displacement mechanisms.
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revisiting metal fluorides as lithium ion battery cathodes
Nature Materials, 2021Co-Authors: Xiao Hua, Alexander S. Eggeman, Rosa Robert, Harry S. Geddes, Chris J. Pickard, Elizabeth CastillomartinezAbstract:Metal fluorides, promising lithium-ion battery cathode materials, have been classified as conversion materials due to the reconstructive phase transitions widely presumed to occur upon lithiation. We challenge this view by studying FeF3 using X-ray total scattering and electron diffraction techniques that measure structure over multiple length scales coupled with density functional theory calculations, and by revisiting prior experimental studies of FeF2 and CuF2. Metal fluoride lithiation is instead dominated by diffusion-controlled displacement mechanisms, and a clear Topological Relationship between the metal fluoride F- sublattices and that of LiF is established. Initial lithiation of FeF3 forms FeF2 on the particle's surface, along with a cation-ordered and stacking-disordered phase, A-LixFeyF3, which is structurally related to α-/β-LiMn2+Fe3+F6 and which topotactically transforms to B- and then C-LixFeyF3, before forming LiF and Fe. Lithiation of FeF2 and CuF2 results in a buffer phase between FeF2/CuF2 and LiF. The resulting principles will aid future developments of a wider range of isomorphic metal fluorides.
Tomohiro Shibata - One of the best experts on this subject based on the ideXlab platform.
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real time estimation of human cloth Topological Relationship using depth sensor for robotic clothing assistance
Robot and Human Interactive Communication, 2014Co-Authors: Nishanth Koganti, Tomoya Tamei, Takamitsu Matsubara, Tomohiro ShibataAbstract:In this study, we propose a novel method for the real-time estimation of Human-Cloth Relationship, which is crucial for efficient motor skill learning in Robotic Clothing Assistance. This system relies on the use of low cost depth sensor, which provides color and depth images without requiring an elaborate setup making it suitable for real-world applications. We present an efficient algorithm to estimate the parameters that represent the Topological Relationship between human and the clothing article. At the core of our approach are low dimensional representation of Human-Cloth Relationship using topology coordinates for fast learning of motor skills and a unified ellipse fitting algorithm for the compact representation of the state of clothing articles. We conducted experiments that illustrate the robustness of these feature representations. Furthermore, we evaluated the performance of our proposed method by applying it to real-time clothing assistance tasks and compared the estimates provided by our method with the ground truth.
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estimation of human cloth Topological Relationship using depth sensor for robotic clothing assistance
Artificial Intelligence Review, 2013Co-Authors: Nishanth Koganti, Tomoya Tamei, Takamitsu Matsubara, Tomohiro ShibataAbstract:In this study we consider the problem of estimating Human-Cloth Topological Relationship using a depth sensor and its application to robotic clothing assistance. In the past, reinforcement learning with low dimensional Topological representations has been used to learn the necessary motor skills to perform clothing. In this framework, motion capture system was used to observe the Human-Cloth Relationship. There were problems faced with the use of motion capture system: 1) Elaborate and expensive setup of the system 2) Occlusion of optical markers by other objects in the environment 3) Observation of non existent markers due to unwanted reflections. To overcome these difficulties, we propose a framework to observe the Human-Cloth Topological Relationship using a depth sensor. We demonstrate that the depth sensor can provide reliable estimates of topology coordinates and can replace the complex and expensive setup of motion capture system.
Xiao Hua - One of the best experts on this subject based on the ideXlab platform.
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Revisiting metal fluorides as lithium-ion battery cathodes
Nature Materials, 2021Co-Authors: Xiao Hua, Alexander S. Eggeman, Elizabeth Castillo-martínez, Rosa Robert, Harry S. Geddes, Chris J. Pickard, Wei Meng, Kamila M. Wiaderek, Nathalie Pereira, Glenn G. AmatucciAbstract:Metal fluorides, promising lithium-ion battery cathode materials, have been classified as conversion materials due to the reconstructive phase transitions widely presumed to occur upon lithiation. We challenge this view by studying FeF_3 using X-ray total scattering and electron diffraction techniques that measure structure over multiple length scales coupled with density functional theory calculations, and by revisiting prior experimental studies of FeF_2 and CuF_2. Metal fluoride lithiation is instead dominated by diffusion-controlled displacement mechanisms, and a clear Topological Relationship between the metal fluoride F^− sublattices and that of LiF is established. Initial lithiation of FeF_3 forms FeF_2 on the particle’s surface, along with a cation-ordered and stacking-disordered phase, A-Li_ x Fe_ y F_3, which is structurally related to α-/β-LiMn^2+Fe^3+F_6 and which topotactically transforms to B- and then C-Li_ x Fe_ y F_3, before forming LiF and Fe. Lithiation of FeF_2 and CuF_2 results in a buffer phase between FeF_2/CuF_2 and LiF. The resulting principles will aid future developments of a wider range of isomorphic metal fluorides. Metal-fluoride-based lithium-ion battery cathodes are typically classified as conversion materials because reconstructive phase transitions are presumed to occur upon lithiation. Metal fluoride lithiation is now shown to be dominated instead by diffusion-controlled displacement mechanisms.
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revisiting metal fluorides as lithium ion battery cathodes
Nature Materials, 2021Co-Authors: Xiao Hua, Alexander S. Eggeman, Rosa Robert, Harry S. Geddes, Chris J. Pickard, Elizabeth CastillomartinezAbstract:Metal fluorides, promising lithium-ion battery cathode materials, have been classified as conversion materials due to the reconstructive phase transitions widely presumed to occur upon lithiation. We challenge this view by studying FeF3 using X-ray total scattering and electron diffraction techniques that measure structure over multiple length scales coupled with density functional theory calculations, and by revisiting prior experimental studies of FeF2 and CuF2. Metal fluoride lithiation is instead dominated by diffusion-controlled displacement mechanisms, and a clear Topological Relationship between the metal fluoride F- sublattices and that of LiF is established. Initial lithiation of FeF3 forms FeF2 on the particle's surface, along with a cation-ordered and stacking-disordered phase, A-LixFeyF3, which is structurally related to α-/β-LiMn2+Fe3+F6 and which topotactically transforms to B- and then C-LixFeyF3, before forming LiF and Fe. Lithiation of FeF2 and CuF2 results in a buffer phase between FeF2/CuF2 and LiF. The resulting principles will aid future developments of a wider range of isomorphic metal fluorides.
Alexander S. Eggeman - One of the best experts on this subject based on the ideXlab platform.
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Revisiting metal fluorides as lithium-ion battery cathodes
Nature Materials, 2021Co-Authors: Xiao Hua, Alexander S. Eggeman, Elizabeth Castillo-martínez, Rosa Robert, Harry S. Geddes, Chris J. Pickard, Wei Meng, Kamila M. Wiaderek, Nathalie Pereira, Glenn G. AmatucciAbstract:Metal fluorides, promising lithium-ion battery cathode materials, have been classified as conversion materials due to the reconstructive phase transitions widely presumed to occur upon lithiation. We challenge this view by studying FeF_3 using X-ray total scattering and electron diffraction techniques that measure structure over multiple length scales coupled with density functional theory calculations, and by revisiting prior experimental studies of FeF_2 and CuF_2. Metal fluoride lithiation is instead dominated by diffusion-controlled displacement mechanisms, and a clear Topological Relationship between the metal fluoride F^− sublattices and that of LiF is established. Initial lithiation of FeF_3 forms FeF_2 on the particle’s surface, along with a cation-ordered and stacking-disordered phase, A-Li_ x Fe_ y F_3, which is structurally related to α-/β-LiMn^2+Fe^3+F_6 and which topotactically transforms to B- and then C-Li_ x Fe_ y F_3, before forming LiF and Fe. Lithiation of FeF_2 and CuF_2 results in a buffer phase between FeF_2/CuF_2 and LiF. The resulting principles will aid future developments of a wider range of isomorphic metal fluorides. Metal-fluoride-based lithium-ion battery cathodes are typically classified as conversion materials because reconstructive phase transitions are presumed to occur upon lithiation. Metal fluoride lithiation is now shown to be dominated instead by diffusion-controlled displacement mechanisms.
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revisiting metal fluorides as lithium ion battery cathodes
Nature Materials, 2021Co-Authors: Xiao Hua, Alexander S. Eggeman, Rosa Robert, Harry S. Geddes, Chris J. Pickard, Elizabeth CastillomartinezAbstract:Metal fluorides, promising lithium-ion battery cathode materials, have been classified as conversion materials due to the reconstructive phase transitions widely presumed to occur upon lithiation. We challenge this view by studying FeF3 using X-ray total scattering and electron diffraction techniques that measure structure over multiple length scales coupled with density functional theory calculations, and by revisiting prior experimental studies of FeF2 and CuF2. Metal fluoride lithiation is instead dominated by diffusion-controlled displacement mechanisms, and a clear Topological Relationship between the metal fluoride F- sublattices and that of LiF is established. Initial lithiation of FeF3 forms FeF2 on the particle's surface, along with a cation-ordered and stacking-disordered phase, A-LixFeyF3, which is structurally related to α-/β-LiMn2+Fe3+F6 and which topotactically transforms to B- and then C-LixFeyF3, before forming LiF and Fe. Lithiation of FeF2 and CuF2 results in a buffer phase between FeF2/CuF2 and LiF. The resulting principles will aid future developments of a wider range of isomorphic metal fluorides.
Nishanth Koganti - One of the best experts on this subject based on the ideXlab platform.
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real time estimation of human cloth Topological Relationship using depth sensor for robotic clothing assistance
Robot and Human Interactive Communication, 2014Co-Authors: Nishanth Koganti, Tomoya Tamei, Takamitsu Matsubara, Tomohiro ShibataAbstract:In this study, we propose a novel method for the real-time estimation of Human-Cloth Relationship, which is crucial for efficient motor skill learning in Robotic Clothing Assistance. This system relies on the use of low cost depth sensor, which provides color and depth images without requiring an elaborate setup making it suitable for real-world applications. We present an efficient algorithm to estimate the parameters that represent the Topological Relationship between human and the clothing article. At the core of our approach are low dimensional representation of Human-Cloth Relationship using topology coordinates for fast learning of motor skills and a unified ellipse fitting algorithm for the compact representation of the state of clothing articles. We conducted experiments that illustrate the robustness of these feature representations. Furthermore, we evaluated the performance of our proposed method by applying it to real-time clothing assistance tasks and compared the estimates provided by our method with the ground truth.
-
estimation of human cloth Topological Relationship using depth sensor for robotic clothing assistance
Artificial Intelligence Review, 2013Co-Authors: Nishanth Koganti, Tomoya Tamei, Takamitsu Matsubara, Tomohiro ShibataAbstract:In this study we consider the problem of estimating Human-Cloth Topological Relationship using a depth sensor and its application to robotic clothing assistance. In the past, reinforcement learning with low dimensional Topological representations has been used to learn the necessary motor skills to perform clothing. In this framework, motion capture system was used to observe the Human-Cloth Relationship. There were problems faced with the use of motion capture system: 1) Elaborate and expensive setup of the system 2) Occlusion of optical markers by other objects in the environment 3) Observation of non existent markers due to unwanted reflections. To overcome these difficulties, we propose a framework to observe the Human-Cloth Topological Relationship using a depth sensor. We demonstrate that the depth sensor can provide reliable estimates of topology coordinates and can replace the complex and expensive setup of motion capture system.
