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1. 发明授权

US08808921B2 Current collector for flexible electrode, method of manufacturing same, and negative electrode including same 有权
标题翻译：柔性电极用集电体及其制造方法以及包含该电极的负极
公开(公告)号：US08808921B2
公开(公告)日：2014-08-19
申请号：US13576703
申请日：2010-05-18
申请人： Soojin Park , Jae-Phil Cho , Hyun-Kon Song , Jung-In Lee
发明人： Soojin Park , Jae-Phil Cho , Hyun-Kon Song , Jung-In Lee
IPC分类号： H01M4/66 , H01M4/13 , H01M4/70 , B32B7/04 , B32B15/09 , B32B15/095 , B32B15/085
CPC分类号： H01M4/661 , B32B7/045 , B32B15/085 , B32B15/09 , B32B15/095 , B32B2457/00 , H01M4/13 , H01M4/667 , H01M4/668 , H01M4/70 , Y02E60/122 , Y02P70/54
摘要： Disclosed are a current collector for a flexible electrode, a method of manufacturing the same, and a negative electrode including the same. The current collector for a flexible electrode includes: a flexible polymer substrate; a cross-linkable polymer layer disposed on the polymer substrate; and a metal layer disposed on the cross-linkable polymer layer, wherein the surface of the cross-linkable polymer layer includes a plurality of protrusions and grooves.
摘要翻译：公开了用于柔性电极的集电器，其制造方法和包括该集电器的负极。用于柔性电极的集电器包括：柔性聚合物基板; 设置在所述聚合物基板上的可交联聚合物层; 以及设置在可交联聚合物层上的金属层，其中可交联聚合物层的表面包括多个突起和凹槽。

2. 发明申请

US20130011742A1 CURRENT COLLECTOR FOR FLEXIBLE ELECTRODE, METHOD OF MANUFACTURING SAME, AND NEGATIVE ELECTRODE INCLUDING SAME 有权
标题翻译：用于柔性电极的电流收集器，其制造方法和包括其的负电极
公开(公告)号：US20130011742A1
公开(公告)日：2013-01-10
申请号：US13576703
申请日：2010-05-18
申请人： Soojin Park , Jae-Phil Cho , Hyun-Kon Song , Jung-In Lee
发明人： Soojin Park , Jae-Phil Cho , Hyun-Kon Song , Jung-In Lee
IPC分类号： H01M4/66 , C25D5/54 , H01M4/04
CPC分类号： H01M4/661 , B32B7/045 , B32B15/085 , B32B15/09 , B32B15/095 , B32B2457/00 , H01M4/13 , H01M4/667 , H01M4/668 , H01M4/70 , Y02E60/122 , Y02P70/54
摘要： Disclosed are a current collector for a flexible electrode, a method of manufacturing the same, and a negative electrode including the same. The current collector for a flexible electrode includes: a flexible polymer substrate; a cross-linkable polymer layer disposed on the polymer substrate; and a metal layer disposed on the cross-linkable polymer layer, wherein the surface of the cross-linkable polymer layer includes a plurality of protrusions and grooves.
摘要翻译：公开了用于柔性电极的集电器，其制造方法和包括该集电器的负极。用于柔性电极的集电器包括：柔性聚合物基板; 设置在所述聚合物基板上的可交联聚合物层; 以及设置在可交联聚合物层上的金属层，其中可交联聚合物层的表面包括多个突起和凹槽。

3. 发明申请

US20120064408A1 POSITIVE ACTIVE MATERIAL FOR RECHARGEABLE LITHIUM BATTERY, METHOD OF PREPARING THE SAME, AND RECHARGEABLE LITHIUM BATTERY INCLUDING THE SAME 审中-公开
标题翻译：用于可充电锂电池的正极活性材料，其制备方法和包括其的可充电锂电池
公开(公告)号：US20120064408A1
公开(公告)日：2012-03-15
申请号：US12909934
申请日：2010-10-22
申请人： Hyun-Kon Song , Myeong-Hee Lee , Jin-Young Kim , Soojin Park , Jaephil Cho
发明人： Hyun-Kon Song , Myeong-Hee Lee , Jin-Young Kim , Soojin Park , Jaephil Cho
IPC分类号： H01M4/485 , H01M4/90 , H01M4/525 , H01M4/583 , H01M4/52
CPC分类号： H01M4/625 , H01M4/136 , H01M4/1397 , H01M4/366 , H01M4/5825 , H01M10/0525
摘要： Provided is a positive active material for a lithium rechargeable battery that includes primary particles including a compound being capable of intercalating and deintercalating lithium, and secondary particles including the primary particles gathered with one another, wherein the secondary particles have a void core structure. A method of preparing the same and a lithium rechargeable battery including the same are also provided.
摘要翻译：提供了一种锂可再充电电池的正极活性材料，其包括一次粒子，其包括能够嵌入和脱嵌锂的化合物，以及包含彼此聚集的一次粒子的二次粒子，其中二次粒子具有空心核心结构。还提供了制备该方法和包含该锂二次电池的锂可再充电电池的方法。

4. 发明授权

US09255973B2 System and method for estimating long term characteristics of battery 有权
标题翻译：估计电池长期特性的系统和方法
公开(公告)号：US09255973B2
公开(公告)日：2016-02-09
申请号：US12674647
申请日：2008-08-21
申请人： Hyun-Kon Song , Jeong-Ju Cho , Yeon-Uk Choo , Mi-Young Son , Ho-Chun Lee
发明人： Hyun-Kon Song , Jeong-Ju Cho , Yeon-Uk Choo , Mi-Young Son , Ho-Chun Lee
IPC分类号： G06E1/00 , G06E3/00 , G06F15/18 , G06G7/00 , G01R31/36 , G06N7/00
CPC分类号： G01R31/3651 , G06N7/00
摘要： A system for estimating long term characteristics of a battery includes a learning data input unit for receiving initial characteristic learning data and long term characteristic learning data of a battery to be a learning object; a measurement data input unit for receiving initial characteristic measurement data of a battery to be an object for estimation of long term characteristics; and an artificial neural network operation unit for receiving the initial characteristic learning data and the long term characteristic learning data from the learning data input unit to allow learning of an artificial neural network, receiving the initial characteristic measurement data from the measurement data input unit and applying the learned artificial neural network thereto, and thus calculating long term characteristic estimation data from the initial characteristic measurement data of the battery and outputting the long term characteristic estimation data.
摘要翻译：一种用于估计电池的长期特性的系统包括用于接收作为学习对象的电池的初始特征学习数据和长期特征学习数据的学习数据输入单元; 测量数据输入单元，用于接收作为用于估计长期特性的对象的电池的初始特性测量数据; 以及人工神经网络操作单元，用于从学习数据输入单元接收初始特征学习数据和长期特征学习数据，以允许学习人造神经网络，从测量数据输入单元接收初始特征测量数据并应用从而从电池的初始特性测量数据计算长期特征估计数据并输出长期特征估计数据。

5. 发明授权

US08412658B2 System and method for estimating long term characteristics of battery 有权
标题翻译：估计电池长期特性的系统和方法
公开(公告)号：US08412658B2
公开(公告)日：2013-04-02
申请号：US12678094
申请日：2008-09-12
申请人： Hyun-Kon Song , Jeong-Ju Cho , Yeon-Uk Choo , Mi-Young Son , Ho-Chun Lee
发明人： Hyun-Kon Song , Jeong-Ju Cho , Yeon-Uk Choo , Mi-Young Son , Ho-Chun Lee
IPC分类号： G06N3/08
CPC分类号： H01M10/482 , G01R31/3651 , G01R31/3679 , H01M10/48
摘要： A system includes a learning data input unit for receiving initial and long term characteristic learning data of a battery to be a learning object; a measurement data input unit for receiving initial characteristic measurement data of a battery to be an object for long term characteristic estimation; an artificial neural network operation unit for converting the learning data into first and second data structures, allowing an artificial neural network to learn the learning data based on each data structure, converting the measurement data into first and second data structures, and individually applying the learned artificial neural network corresponding to each data structure to calculate and output long term characteristic estimation data based on each data structure; and a long term characteristic evaluation unit for calculating an error of the estimation data of each data structure and determining reliability of the estimation data depending on error.
摘要翻译：一种系统，包括用于接收作为学习对象的电池的初始和长期特征学习数据的学习数据输入单元; 测量数据输入单元，用于接收作为长期特性估计对象的电池的初始特性测量数据; 一种用于将学习数据转换为第一和第二数据结构的人造神经网络操作单元，允许人造神经网络基于每个数据结构学习学习数据，将测量数据转换为第一和第二数据结构，以及单独应用所学习的对应于每个数据结构的人工神经网络，基于每个数据结构计算和输出长期特征估计数据; 以及长期特征评估单元，用于计算每个数据结构的估计数据的误差，并根据误差确定估计数据的可靠性。

6. 发明授权

US08435696B2 Redox-active polymers and their applications 有权
标题翻译：氧化还原活性聚合物及其应用
公开(公告)号：US08435696B2
公开(公告)日：2013-05-07
申请号：US12905398
申请日：2010-10-15
申请人： G. Tayhas R. Palmore , Jiangfeng Fei , Hyun-Kon Song
发明人： G. Tayhas R. Palmore , Jiangfeng Fei , Hyun-Kon Song
IPC分类号： H01M8/10
CPC分类号： H01M8/16 , H01M4/8807 , H01M4/8853 , H01M4/9008 , Y02E60/527
摘要： The present invention is directed to a redox-active, conducting polymer energy storage system, said system including an electrode and a counter electrode, wherein the electrode comprises a first conducting polymer and the counter electrode comprises a second conducting polymer, wherein the first conducting polymer is doped by at least one or more first redox-active compounds and/or by a polymer and/or a co-polymer of the one or more first redox-active compounds and the second conducting polymer is doped by at least one or more second redox-active compounds and/or by a polymer and/or a co-polymer of the one or more second redox-active compounds, and wherein there is a potential difference between the dopant for the electrode and the dopant for the counter electrode. In one preferred embodiment, the first or the second redox-active compound is 2,2′-azinobis(3-ethylbenzothiazoline-6-sulfonate) (ABTS). In another preferred embodiment, an exemplary redox-active compound is a polymerizable derivative of ABTS or a polymer or co-polymer of this monomer.
摘要翻译：本发明涉及氧化还原活性导电聚合物储能系统，所述系统包括电极和对电极，其中所述电极包括第一导电聚合物，所述对电极包括第二导电聚合物，其中所述第一导电聚合物由至少一种或多种第一氧化还原活性化合物和/或通过一种或多种第一种氧化还原活性化合物和第二导电聚合物的聚合物和/或共聚物掺杂至少一个或多个第二氧化还原活性化合物和/或一种或多种第二种氧化还原活性化合物的聚合物和/或共聚物，并且其中在电极的掺杂剂和对电极的掺杂剂之间存在电位差。在一个优选的实施方案中，第一或第二氧化还原活性化合物是2,2'-氮杂双（3-乙基苯并噻唑啉-6-磺酸盐）（ABTS）。在另一个优选的实施方案中，示例性氧化还原活性化合物是ABTS的可聚合衍生物或该单体的聚合物或共聚物。

7. 发明申请

US20110191278A1 SYSTEM AND METHOD FOR ESTIMATING LONG TERM CHARACTERISTICS OF BATTERY 有权
标题翻译：用于估计电池长期特性的系统和方法
公开(公告)号：US20110191278A1
公开(公告)日：2011-08-04
申请号：US12674647
申请日：2008-08-21
申请人： Hyun-Kon Song , Jeong-ju Cho , Yeon-Uk Choo , Mi-Young Son , Ho-Chun Lee
发明人： Hyun-Kon Song , Jeong-ju Cho , Yeon-Uk Choo , Mi-Young Son , Ho-Chun Lee
IPC分类号： G06N3/08
CPC分类号： G01R31/3651 , G06N7/00
摘要： A system for estimating long term characteristics of a battery includes a learning data input unit for receiving initial characteristic learning data and long term characteristic learning data of a battery to be a learning object; a measurement data input unit for receiving initial characteristic measurement data of a battery to be an object for estimation of long term characteristics; and an artificial neural network operation unit for receiving the initial characteristic learning data and the long term characteristic learning data from the learning data input unit to allow learning of an artificial neural network, receiving the initial characteristic measurement data from the measurement data input unit and applying the learned artificial neural network thereto, and thus calculating long term characteristic estimation data from the initial characteristic measurement data of the battery and outputting the long term characteristic estimation data.
摘要翻译：一种用于估计电池的长期特性的系统包括用于接收作为学习对象的电池的初始特征学习数据和长期特征学习数据的学习数据输入单元; 测量数据输入单元，用于接收作为用于估计长期特性的对象的电池的初始特性测量数据; 以及人工神经网络操作单元，用于从学习数据输入单元接收初始特征学习数据和长期特征学习数据，以允许学习人造神经网络，从测量数据输入单元接收初始特征测量数据并应用从而从电池的初始特性测量数据计算长期特征估计数据并输出长期特征估计数据。

8. 发明申请

US20110031440A1 REDOX-ACTIVE POLYMERS AND THEIR APPLICATIONS 有权
标题翻译：氧化还原活性聚合物及其应用
公开(公告)号：US20110031440A1
公开(公告)日：2011-02-10
申请号：US12905398
申请日：2010-10-15
申请人： G. Tayhas R. Palmore , Jiangfeng Fei , Hyun-Kon Song
发明人： G. Tayhas R. Palmore , Jiangfeng Fei , Hyun-Kon Song
IPC分类号： H01B1/12
CPC分类号： H01M8/16 , H01M4/8807 , H01M4/8853 , H01M4/9008 , Y02E60/527
摘要： The present invention is directed to a redox-active, conducting polymer energy storage system, said system including an electrode and a counter electrode, wherein the electrode comprises a first conducting polymer and the counter electrode comprises a second conducting polymer, wherein the first conducting polymer is doped by at least one or more first redox-active compounds and/or by a polymer and/or a co-polymer of the one or more first redox-active compounds and the second conducting polymer is doped by at least one or more second redox-active compounds and/or by a polymer and/or a co-polymer of the one or more second redox-active compounds, and wherein there is a potential difference between the dopant for the electrode and the dopant for the counter electrode. In one preferred embodiment, the first or the second redox-active compound is 2,2′-azinobis(3-ethylbenzothiazoline-6-sulfonate) (ABTS). In another preferred embodiment, an exemplary redox-active compound is a polymerizable derivative of ABTS or a polymer or co-polymer of this monomer.
摘要翻译：本发明涉及氧化还原活性导电聚合物储能系统，所述系统包括电极和对电极，其中所述电极包括第一导电聚合物，所述对电极包括第二导电聚合物，其中所述第一导电聚合物由至少一种或多种第一氧化还原活性化合物和/或通过一种或多种第一种氧化还原活性化合物和第二导电聚合物的聚合物和/或共聚物掺杂至少一个或多个第二氧化还原活性化合物和/或一种或多种第二种氧化还原活性化合物的聚合物和/或共聚物，并且其中在电极的掺杂剂和对电极的掺杂剂之间存在电位差。在一个优选的实施方案中，第一或第二氧化还原活性化合物是2,2'-氮杂双（3-乙基苯并噻唑啉-6-磺酸盐）（ABTS）。在另一个优选的实施方案中，示例性氧化还原活性化合物是ABTS的可聚合衍生物或该单体的聚合物或共聚物。

9. 发明授权

US07838687B2 Redox-active polymers and their applications 有权
标题翻译：氧化还原活性聚合物及其应用
公开(公告)号：US07838687B2
公开(公告)日：2010-11-23
申请号：US11512430
申请日：2006-08-29
申请人： G. Tayhas R. Palmore , Jiangfeng Fei , Hyun-Kon Song
发明人： G. Tayhas R. Palmore , Jiangfeng Fei , Hyun-Kon Song
IPC分类号： C07D293/00 , C07D417/02
CPC分类号： H01M8/16 , H01M4/8807 , H01M4/8853 , H01M4/9008 , Y02E60/527
摘要： The present invention provides a monomer comprising the structure: wherein R1 and/or R1′ are selected from the group consisting of MeO, EtO, COF3, SO4H, SO3−, SO3H, H, CHNO4S2F3, C5H4N2O6S2F6, C10H10N4S2, CH3, n-Bu, Cl, NH2, EtN, Br, alkyl, ether, ester, sulfonate, ammonium, carboxylate, phosphonate and any combination thereof, R2 and/or R2′, are selected from the group consisting of EtO, SO3H, H, C10H10N4S2, CH3, Cl, C6H14N2S and any combination thereof, R3 and/or R3′ are selected from the group consisting of CH3, Cl, H and any combination thereof, and R4 and/or R4′ are selected from the group consisting of CH3, H, C2H5, C4H9, C6H5, C8H17, C2H5S, C3H7S, C4H8Br, C10H23N, C20H21N2, C18H25N2, C21H23N2, C31H29N2O2, C22H25N4, C20H25N2, C3H7OS, and any combination thereof.
摘要翻译：本发明提供一种包含以下结构的单体：其中R1和/或R1'选自MeO，EtO，COF3，SO4H，SO3-，SO3H，H，CHNO4S2F3，C5H4N2O6S2F6，C10H10N4S2，CH3，n-Bu ，Cl，NH2，EtN，Br，烷基，醚，酯，磺酸盐，铵，羧酸盐，膦酸盐及其任何组合，R2和/或R2'选自EtO，SO3H，H，C10H10N4S2，CH3 ，Cl，C 6 H 14 N 2 S及其任何组合，R 3和/或R 3'选自CH 3，Cl，H及其任何组合，并且R 4和/或R 4'选自CH 3，H， C2H5，C4H9，C6H5，C8H17，C2H5S，C3H7S，C4H8Br，C10H23N，C20H21N2，C18H25N2，C21H23N2，C31H29N2O2，C22H25N4，C20H25N2，C3H7OS及其任意组合。

10. 发明申请

US20100312733A1 SYSTEM AND METHOD FOR ESTIMATING LONG TERM CHARACTERISTICS OF BATTERY 有权
标题翻译：用于估计电池长期特性的系统和方法
公开(公告)号：US20100312733A1
公开(公告)日：2010-12-09
申请号：US12678094
申请日：2008-09-12
申请人： Hyun-Kon Song , Jeong-Ju Cho , Yeon-Uk Choo , Mi-Young Son , Ho-Chun Lee
发明人： Hyun-Kon Song , Jeong-Ju Cho , Yeon-Uk Choo , Mi-Young Son , Ho-Chun Lee
IPC分类号： G06N3/08 , G06F3/048 , G01R31/36 , G06F19/00
CPC分类号： H01M10/482 , G01R31/3651 , G01R31/3679 , H01M10/48
摘要： A system includes a learning data input unit for receiving initial and long term characteristic learning data of a battery to be a learning object; a measurement data input unit for receiving initial characteristic measurement data of a battery to be an object for long term characteristic estimation; an artificial neural network operation unit for converting the learning data into first and second data structures, allowing an artificial neural network to learn the learning data based on each data structure, converting the measurement data into first and second data structures, and individually applying the learned artificial neural network corresponding to each data structure to calculate and output long term characteristic estimation data based on each data structure; and a long term characteristic evaluation unit for calculating an error of the estimation data of each data structure and determining reliability of the estimation data depending on error.
摘要翻译：一种系统，包括用于接收作为学习对象的电池的初始和长期特征学习数据的学习数据输入单元; 测量数据输入单元，用于接收作为长期特性估计对象的电池的初始特性测量数据; 一种用于将学习数据转换为第一和第二数据结构的人造神经网络操作单元，允许人造神经网络基于每个数据结构学习学习数据，将测量数据转换为第一和第二数据结构，以及单独应用所学习的对应于每个数据结构的人工神经网络，基于每个数据结构计算和输出长期特征估计数据; 以及长期特征评估单元，用于计算每个数据结构的估计数据的误差，并根据误差确定估计数据的可靠性。

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