Advanced Materials2026,Vol.38Issue(13) :e20337.1-e20337.12.DOI:10.1002/adma.202520337

Engineering Electronic Radial Effects for Fast Li~+ Transport in Solid-State Electrolytes

Jiadong Shen Gilseob Kim Jong-woan Chung Sunjae Kwon Wootack Chung Dahye Yoon Xiwen Zhang Lei Shen Junjie Chen Jun Liu Yong-Mook Kang
Advanced Materials2026,Vol.38Issue(13) :e20337.1-e20337.12.DOI:10.1002/adma.202520337

Engineering Electronic Radial Effects for Fast Li~+ Transport in Solid-State Electrolytes

Jiadong Shen 1Gilseob Kim 1Jong-woan Chung 1Sunjae Kwon 1Wootack Chung 1Dahye Yoon 1Xiwen Zhang 2Lei Shen 3Junjie Chen 4Jun Liu 5Yong-Mook Kang6
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作者信息

  • 1. Department of Materials Science and Engineering, Korea University, Seoul, Republic of Korea
  • 2. Department of Mechanical Engineering, National University of Singapore, Singapore, Singapore||School of Mechanical Engineering, Southeast University, Nanjing, China
  • 3. Department of Mechanical Engineering, National University of Singapore, Singapore, Singapore
  • 4. Department of Mechanical and Aerospace Engineering, The Hong Kong University of Science and Technology, Singapore, Hong Kong SAR, China
  • 5. Department of Materials Science and Engineering, South China University of Technology, Guangzhou, Guangdong, China
  • 6. Department of Materials Science and Engineering, Korea University, Seoul, Republic of Korea||KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul, Republic of Korea||Department of Battery-Smart Factory, Korea University, Seoul, Republic of Korea
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Abstract

Achieving high Li~+ conductivity, near-unity transference numbers, and stable interfaces in solid-state electrolytes remains amajor challenge for lithium-metal batteries. Here we introduce a radial-effect design principle: relativistic expansion and spin–orbit coupling of 5d orbitals enhance s–d/p–d hybridization, weaken Li–anion interactions, and lower migration barriers. An entropybased descriptor, S_d, trained and validated with machine learning across >10,000 oxides, sulfides, and halides captures this effect. Machine-learning-guided high-throughput screening flags monoclinic HfO_2,whose 5d~2 radial expansion lowersmigration barriers by ∼45% vs Sc_2O_3 or Y_2O_3. Guided by this insight,we employmillisecond flash-Joule heating to convert HfO_2 into nanosized single crystals, then embed them in a Li-conductive binder to create sc-HfO_2@LCB, whose radial coupling yields interconnected Li~+ pathways (1.23 mS cm~(-1), 30℃; t_(Li+) = 0.82, 25℃) and a 4.8 V electrochemical window. Operando Raman/XANES confirms faster Li+ transport. Consequently, 2 Ah LiNi_(0.9)Co_(0.05)Mn_(0.05)O_2‖Li pouch cells deliver ∼472 Wh kg~(-1) (stack-level), maintain superior rate capability over hundreds of cycles, and survive 150℃ hot-plate tests. These results establish radial-effect engineering as a sophisticated strategy for high-performance, thermally resilient solid-state batteries.

Key words

entropy-based descriptor/Flash Joule Heating/machine-learning/radial-effect engineering/s-d/p-d hybridizations

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出版年

2026
Advanced Materials

Advanced Materials

ISSN:0935-9648
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