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High-throughput methods based on automation technology and computer technology can quickly provide tens of thousands of scientific research data, which poses a new challenge to the scientific and efficient management of scientific data. Rechargeable secondary batteries are the keys to the development of electric vehicles and the first choice of wind/photoelectric energy storage. The discovery of new battery materials plays an important role in improving the performance of the secondary batteries. New methods based on big date can be introduced into the screening and design of battery materials to accelerate the development of secondary batteries. This work introduces the development and application of battery material database from the aspects of data acquisition, construction of general and specific battery material database, and the challenges faced by the battery material database.
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Keywords:
- battery materials /
- high-throughput calculations /
- database /
- materials genome
[1] Armand M, Tarascon J M 2008 Nature 451 652Google Scholar
[2] Chen R S, Li Q H, Yu X Q, Chen L Q, Li H 2020 Chem. Rev. 120 6820Google Scholar
[3] Jain A, Persson K A, Ceder G 2016 APL Mater. 4 053102Google Scholar
[4] Suh C, Fare C, Warren J A, Pyzer-Knapp E O 2020 Annu. Rev. Mater. Res. 50 1Google Scholar
[5] Mueller T, Hautier G, Jain A, Ceder G 2011 Chem. Mater. 23 3854Google Scholar
[6] Kirklin S, Meredig, Wolverton C 2013 Adv. Energy Mater. 3 252Google Scholar
[7] Xiao R J, Li H, Chen L Q 2015 Sci. Rep. 5 14227Google Scholar
[8] Rasmussen F A, Thygesen K S 2015 J. Phys. Chem. C 119 13169Google Scholar
[9] Sikora B J, Wilmer C E, Greenfield M L, Snurr R Q 2011 Chem. Sci. 3 2217Google Scholar
[10] Ashton M, Paul J, Sinnott S B, Hennig R G 2017 Phys. Rev. Lett. 118 106101Google Scholar
[11] http://e01.iphy.ac.cn/bmd [2020-9-17]
[12] Zhang L W, He B, Zhao Q, Zou Z Y, Chi S T, Mi P H, Ye A J, Li Y J, Wang D, Avdeev M, Adams S, Shi S Q 2020 Adv. Funct. Mater. 30 2003087Google Scholar
[13] Korbel S, Marques M A L, Botti S 2016 J. Mater. Chem. C 4 3157Google Scholar
[14] Avdeev M, Sale M, Adams S, Rao R P 2012 Solid State Ionics 225 43Google Scholar
[15] Gaultois M W, Sparks T D, Borg C K H, Seshadri R, Bonificio W D, Clarke D R 2013 Chem. Mater. 25 2911Google Scholar
[16] Carrete J, Li W, Mingo N 2014 Phys. Rev. X 4 011019Google Scholar
[17] Deem M W, Pophale R, Cheeseman P A, Earl D J 2009 J. Phys. Chem. C 113 21353Google Scholar
[18] Zhang T T, Jiang Y, Song Z D, Huang H, He Y Q, Fang Z, Weng H M, Fang C 2019 Nature 566 475Google Scholar
[19] Jain A, Ong S P, Hautier G, Chen W, Richards W D, Dacek S, Cholia S, Gunter D, Skinner D, Ceder G, Persson K A 2013 APL Mater. 1 011002Google Scholar
[20] Curtarolo S, Setyawan W, Hart G L W 2012 Comput. Mater. Sci. 58 218Google Scholar
[21] Saal J E, Kirklin S, Aykol M, Meredig B, Wolverton C 2013 JOM 65 1501Google Scholar
[22] https://atomly.net [2020-9-17]
[23] Ghadbeigi L, Harada J K, Lettiere B R, Sparks T D 2015 Energy Environ. Sci. 8 1640Google Scholar
[24] Huang S, Cole J M 2020 Sci. Data 7 260Google Scholar
[25] Li Y S, Qi Y 2019 Energy Environ. Sci. 12 1286Google Scholar
[26] Tian H K, Chakraborty A, Talin A, Eisenlohr P, Qi Y 2020 J. Electrochem. Soc. 167 090541Google Scholar
[27] 彭佳悦, 祖晨曦, 李泓 2013 储能科学与技术 2 55Google Scholar
Peng J Y, Zu C X, Li H 2013 Energy Storage Sci. Technol. 2 55Google Scholar
[28] Zu C X, Li H 2011 Energy Environ. Sci. 4 2614Google Scholar
[29] 吴娇杨, 刘品, 胡勇胜, 李泓 2016 储能科学与技术 5 443Google Scholar
Wu J Y, Liu P, Hu Y S, Li H 2016 Energy Storage Sci. Technol. 5 443Google Scholar
[30] Wang L, Wu Z, Zou J, Gao P, Niu X, Li H, Chen L 2019 Joule 3 2086Google Scholar
[31] Cao W, Zhang J, Li H 2020 Energy Storage Mater. 26 46Google Scholar
[32] Ceder G 2011 MRS Bulletin 35 693Google Scholar
[33] Kirklin S, Saal J E, Meredig B, Thompson A, Doak J W, Aykol M, Rühl S, Wolverton C 2015 NPJ. Comput. Mater. 1 15010Google Scholar
[34] Jain A, Hautier G, Ong S P, Persson K 2016 J. Mater. Res. 31 977Google Scholar
[35] Hachmann J, Olivares-Amaya R, Atahan-Evrenk S, Amador-Bedolla C, Sánchez-Carrera R S, Gold-Parker A, Vogt L, Brockway A M, Aspuru-Guzik A 2011 J. Phys. Chem. Lett. 2 2241Google Scholar
[36] Shi S Q, Gao J, Liu Y, Zhao Y, Wu Q, Ju W W, Ouyang C Y, Xiao R J 2016 Chin. Phys. B 25 018212Google Scholar
[37] He B, Chi S, Ye A J, Mi P H, Zhang L W, Pu B W, Zou Z Y, Ran Y B, Zhao Q, Wang D, Zhang W Q, Zhao J T, Adams S, Avdeev M, Shi S 2020 Sci. Data 7 151Google Scholar
[38] Nuspl G, Takeuchi T, Weiß A, Kageyama H, Yoshizawa K, Yamabe T 1999 J. Appl. Phys. 86 5484Google Scholar
[39] He B, Ye A J, Chi S, Mi P H, Ran Y B, Zhang L W, Zou X X, Pu B W, Zhao Q, Zou Z Y, Wang D, Zhang W Q, Zhao J T, Avdeev M, Shi S 2020 Sci. Data 7 153Google Scholar
[40] Adams S, Rao R P 2011 Phys. Status Solidi A 208 1746Google Scholar
[41] Henkelman G, Jonsson H 2000 J. Chem. Phys. 113 9978Google Scholar
[42] Kirklin S, Meredig B, Wolverton C 2013 Advanced Energy Materials 3 252
[43] Zhu Y, He X, Mo Y 2017 Adv. Sci. (Weinh) 4 1600517Google Scholar
[44] Wang X L, Xiao R J, Li H, Chen L Q 2016 Phys. Chem. Chem. Phys. 18 21269Google Scholar
[45] Sendek A D, Cubuk E D, Antoniuk E R, Cheon G, Cui Y, Reed E J 2018 Chem. Mater. 31 342Google Scholar
[46] Liu B, Yang J, Yang H, Ye C, Mao Y, Wang J, Shi S, Yang J, Zhang W 2019 J. Mater. Chem. A 7 19961Google Scholar
[47] Wang A P, Kadam S, Li H, Shi S Q 2018 NPJ Comput. Mater. 4 15Google Scholar
[48] Liu Y, Zhao T L, Ju W W, Shi S Q 2017 J. Materiomics 3 159Google Scholar
[49] Liu Y, Guo B R, Zou X X, Li Y J, Shi S Q 2020 Energy Storage Mater. 31 434Google Scholar
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表 1 高通量计算所能获得的材料性质
Table 1. Properties achieved by high-throughput calculations.
计算数据 物化性质 材料种类 总能量 相图、反应路径、形成能 热力学稳定材料 电子结构 带隙、电子传输、电荷分布 特定电学性质材料 原子磁矩 磁构型、磁矩、磁阻等 磁性材料 声子谱 晶格振动、红外吸收谱 动力学稳定材料 力学模量 弹性模量、泊松比等 力学材料 复数介电常数 介电性质 介电材料 反射系数 反射/吸收率 光学材料 吸附能/位置 表面吸附过程 材料表面设计 晶格匹配 界面力学/界面化学稳定性 材料界面设计 离子扩散 离子迁移路径、势垒等 离子导体 表 2 国内外典型的通用型计算材料数据库及公开发布的高通量计算软件[19-22]
Table 2. Typical database forcomputational materials[19-22].
数据库名称 高通量计算软件 Materials Project Pymatgen AFLOWLIB AFLOW OQMD OQMD Atomly — 表 3 机器学习模型应用于二次电池的构效关系
Table 3. Application of machine learning method in the research of secondary batteries.
关心的问题 输入量(描述符) 输出量
(目标性质)固态电解质 原子结构以及它们的XRD
图像信息、化学键数目、
子晶格化学键的离子性、
原子配位数、键长、位能、
熔点、沸点…离子电
导率或
离子迁
移能聚合物电解质 化学结构、组成比率、处理
温度、Mordred描述因子…离子电导率 锂电极 化学键、原子半径、单位
原子体积、质量密度、
子晶格电负性、Li原子
周围原子数变化…热力学
相稳定性界面 热力学稳定性、结构
和动力学参数…界面态 电池制造 活性材料质量比率、
粘性、固液比率…孔隙率和电极
的质量负载表 4 不同层级的数据库类型、用途和使用方法
Table 4. TType, application and usage of battery materials database in various scales.
层级 数据库类型 用途 使用方法 原子尺度 基于理想材料模型获得的
材料在原子尺度的本征性质数据了解所选用材料本身所
具备的性质特征查询及挖掘原子结构及对应的电子结构、离子输运势垒等数据, 帮助寻找到具有目标物性的材料 微观尺度 引入实际材料中的缺陷和微观
构型后获得的实际材料性质数据了解微观结构对材
料性质的调制查询及挖掘缺陷、粒径大小、颗粒形状、比表面积等一系列变量描述下的材料性质数据, 帮助实现对所选材料的性质改善 外场效应 随电场、温度等外场条件改
变时获得的材料性质数据了解材料性质对外
界环境的响应查询及挖掘材料性质数据随外场条件的变化函数, 帮助设计电化学稳定的电池材料 多相作用 将单一材料性质数据扩展到
多种材料之间相互作用的性质数据了解界面等由多相作用
所决定的性质数据查询及挖掘电池中界面的组分、性质数据, 帮助选取相匹配的组成电池的各种材料 宏观尺度 电池器件的性能数据及充放
电过程中电池材料的性质数据实现材料性质数据与电
池器件性能的关联查询及挖掘上述四层性质数据与电池器件性能之间的联系, 帮助实现从材料到电池的整体设计 -
[1] Armand M, Tarascon J M 2008 Nature 451 652Google Scholar
[2] Chen R S, Li Q H, Yu X Q, Chen L Q, Li H 2020 Chem. Rev. 120 6820Google Scholar
[3] Jain A, Persson K A, Ceder G 2016 APL Mater. 4 053102Google Scholar
[4] Suh C, Fare C, Warren J A, Pyzer-Knapp E O 2020 Annu. Rev. Mater. Res. 50 1Google Scholar
[5] Mueller T, Hautier G, Jain A, Ceder G 2011 Chem. Mater. 23 3854Google Scholar
[6] Kirklin S, Meredig, Wolverton C 2013 Adv. Energy Mater. 3 252Google Scholar
[7] Xiao R J, Li H, Chen L Q 2015 Sci. Rep. 5 14227Google Scholar
[8] Rasmussen F A, Thygesen K S 2015 J. Phys. Chem. C 119 13169Google Scholar
[9] Sikora B J, Wilmer C E, Greenfield M L, Snurr R Q 2011 Chem. Sci. 3 2217Google Scholar
[10] Ashton M, Paul J, Sinnott S B, Hennig R G 2017 Phys. Rev. Lett. 118 106101Google Scholar
[11] http://e01.iphy.ac.cn/bmd [2020-9-17]
[12] Zhang L W, He B, Zhao Q, Zou Z Y, Chi S T, Mi P H, Ye A J, Li Y J, Wang D, Avdeev M, Adams S, Shi S Q 2020 Adv. Funct. Mater. 30 2003087Google Scholar
[13] Korbel S, Marques M A L, Botti S 2016 J. Mater. Chem. C 4 3157Google Scholar
[14] Avdeev M, Sale M, Adams S, Rao R P 2012 Solid State Ionics 225 43Google Scholar
[15] Gaultois M W, Sparks T D, Borg C K H, Seshadri R, Bonificio W D, Clarke D R 2013 Chem. Mater. 25 2911Google Scholar
[16] Carrete J, Li W, Mingo N 2014 Phys. Rev. X 4 011019Google Scholar
[17] Deem M W, Pophale R, Cheeseman P A, Earl D J 2009 J. Phys. Chem. C 113 21353Google Scholar
[18] Zhang T T, Jiang Y, Song Z D, Huang H, He Y Q, Fang Z, Weng H M, Fang C 2019 Nature 566 475Google Scholar
[19] Jain A, Ong S P, Hautier G, Chen W, Richards W D, Dacek S, Cholia S, Gunter D, Skinner D, Ceder G, Persson K A 2013 APL Mater. 1 011002Google Scholar
[20] Curtarolo S, Setyawan W, Hart G L W 2012 Comput. Mater. Sci. 58 218Google Scholar
[21] Saal J E, Kirklin S, Aykol M, Meredig B, Wolverton C 2013 JOM 65 1501Google Scholar
[22] https://atomly.net [2020-9-17]
[23] Ghadbeigi L, Harada J K, Lettiere B R, Sparks T D 2015 Energy Environ. Sci. 8 1640Google Scholar
[24] Huang S, Cole J M 2020 Sci. Data 7 260Google Scholar
[25] Li Y S, Qi Y 2019 Energy Environ. Sci. 12 1286Google Scholar
[26] Tian H K, Chakraborty A, Talin A, Eisenlohr P, Qi Y 2020 J. Electrochem. Soc. 167 090541Google Scholar
[27] 彭佳悦, 祖晨曦, 李泓 2013 储能科学与技术 2 55Google Scholar
Peng J Y, Zu C X, Li H 2013 Energy Storage Sci. Technol. 2 55Google Scholar
[28] Zu C X, Li H 2011 Energy Environ. Sci. 4 2614Google Scholar
[29] 吴娇杨, 刘品, 胡勇胜, 李泓 2016 储能科学与技术 5 443Google Scholar
Wu J Y, Liu P, Hu Y S, Li H 2016 Energy Storage Sci. Technol. 5 443Google Scholar
[30] Wang L, Wu Z, Zou J, Gao P, Niu X, Li H, Chen L 2019 Joule 3 2086Google Scholar
[31] Cao W, Zhang J, Li H 2020 Energy Storage Mater. 26 46Google Scholar
[32] Ceder G 2011 MRS Bulletin 35 693Google Scholar
[33] Kirklin S, Saal J E, Meredig B, Thompson A, Doak J W, Aykol M, Rühl S, Wolverton C 2015 NPJ. Comput. Mater. 1 15010Google Scholar
[34] Jain A, Hautier G, Ong S P, Persson K 2016 J. Mater. Res. 31 977Google Scholar
[35] Hachmann J, Olivares-Amaya R, Atahan-Evrenk S, Amador-Bedolla C, Sánchez-Carrera R S, Gold-Parker A, Vogt L, Brockway A M, Aspuru-Guzik A 2011 J. Phys. Chem. Lett. 2 2241Google Scholar
[36] Shi S Q, Gao J, Liu Y, Zhao Y, Wu Q, Ju W W, Ouyang C Y, Xiao R J 2016 Chin. Phys. B 25 018212Google Scholar
[37] He B, Chi S, Ye A J, Mi P H, Zhang L W, Pu B W, Zou Z Y, Ran Y B, Zhao Q, Wang D, Zhang W Q, Zhao J T, Adams S, Avdeev M, Shi S 2020 Sci. Data 7 151Google Scholar
[38] Nuspl G, Takeuchi T, Weiß A, Kageyama H, Yoshizawa K, Yamabe T 1999 J. Appl. Phys. 86 5484Google Scholar
[39] He B, Ye A J, Chi S, Mi P H, Ran Y B, Zhang L W, Zou X X, Pu B W, Zhao Q, Zou Z Y, Wang D, Zhang W Q, Zhao J T, Avdeev M, Shi S 2020 Sci. Data 7 153Google Scholar
[40] Adams S, Rao R P 2011 Phys. Status Solidi A 208 1746Google Scholar
[41] Henkelman G, Jonsson H 2000 J. Chem. Phys. 113 9978Google Scholar
[42] Kirklin S, Meredig B, Wolverton C 2013 Advanced Energy Materials 3 252
[43] Zhu Y, He X, Mo Y 2017 Adv. Sci. (Weinh) 4 1600517Google Scholar
[44] Wang X L, Xiao R J, Li H, Chen L Q 2016 Phys. Chem. Chem. Phys. 18 21269Google Scholar
[45] Sendek A D, Cubuk E D, Antoniuk E R, Cheon G, Cui Y, Reed E J 2018 Chem. Mater. 31 342Google Scholar
[46] Liu B, Yang J, Yang H, Ye C, Mao Y, Wang J, Shi S, Yang J, Zhang W 2019 J. Mater. Chem. A 7 19961Google Scholar
[47] Wang A P, Kadam S, Li H, Shi S Q 2018 NPJ Comput. Mater. 4 15Google Scholar
[48] Liu Y, Zhao T L, Ju W W, Shi S Q 2017 J. Materiomics 3 159Google Scholar
[49] Liu Y, Guo B R, Zou X X, Li Y J, Shi S Q 2020 Energy Storage Mater. 31 434Google Scholar
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