Research Digest — 2026-07-11¶
Halide Solid Electrolytes¶
1. Polyanion-stabilized amorphous halide electrolytes with low lithium content for all-solid-state lithium batteries¶
Source: Nature Communications (s41467-026-69737-x) · 📅 2026-07-08 · ↗ Open paper
Introduces a polyanion-stabilization strategy (Li₂SO₄–ZrCl₄ system) to achieve high ionic conductivity in amorphous halide electrolytes while reducing lithium content below conventional thresholds. The 0.5Li₂SO₄–ZrCl₄ composition achieves competitive conductivity with significantly lower raw material costs compared to state-of-the-art halide and sulfide SEs, challenging the paradigm that high Li content is essential for fast ion conduction.
Relevance to DENG.Group
Directly relevant to Yan Li and Mengke Li's halide electrolyte work — new design strategy via polyanion incorporation that could open a compositional space orthogonal to current group research.
2. Design Principles for Aqueous Stability of Lithium Halide and Oxyhalide Solid Electrolytes¶
Source: ACS Energy Letters (acsenergylett.6c00623) · 📅 2026-06-30 · ↗ Open paper
Establishes design principles for moisture-resistant halide solid electrolytes by analyzing thermodynamic stability against hydrolysis across different halide and oxyhalide chemistries. Identifies specific compositional descriptors that govern aqueous stability, providing rational guidelines for designing air-stable halide SEs.
Relevance to DENG.Group
Highly relevant to Yan Li and Mengke Li's halide electrolyte degradation studies — the stability design principles could directly inform their ongoing work on halide degradation mechanisms.
3. Comparative Advances in Sulfide and Halide Electrolytes for All-Solid-State Lithium Batteries¶
Source: Advanced Materials (adma.202513255) · 📅 2026-06-20 · ↗ Open paper
Comprehensive review comparing sulfide- and halide-based solid electrolytes for ASSBs, systematically evaluating ionic conductivity, electrochemical stability windows, interfacial compatibility, and processability. Highlights that halides offer superior oxidative stability for high-voltage cathodes while sulfides maintain advantages in anode compatibility.
Relevance to DENG.Group
Provides group-wide context for electrolyte selection strategies — directly relevant to Yan Li/Mengke Li (halides) and useful comparative framing for polymer/sulfide crossover work.
4. From powder to product: a perspective on halide electrolytes for commercial lithium solid-state batteries¶
Source: Tungsten / Springer (s42864-026-00378-9) · 📅 2026-06-25 · ↗ Open paper
Commercialization-focused perspective covering structure–property relationships across trigonal, spinel, and oxyhalide frameworks. Discusses scalable synthesis pathways (mechanochemical milling to melt processing), integration strategies for composite electrodes, and full-cell architectures with manufacturability metrics relevant to commercialization. Includes a comparative roadmap versus sulfide and oxide systems.
Relevance to DENG.Group
Important translational perspective for the group's halide work — bridges lab-scale findings to manufacturing considerations, useful for Jerry's strategic positioning of the group's halide research program.
ML Interatomic Potentials¶
5. Machine-learning interatomic potentials for interfaces in all-solid-state batteries: Perspectives on training data, model selection, and validation¶
Source: MRS Communications (OSTI 3024472) · 📅 2026-02-18 · ↗ Open paper
Comprehensive LLNL perspective on MLIP development for grain boundaries and interfaces in ASSBs, focusing on three pillars: data generation, model selection, and validation. Reviews current MLIP applications for GBs and interfaces, highlighting best practices for constructing diverse training datasets and choosing ML architectures for chemically complex interface environments.
Relevance to DENG.Group
Essential reading for the group's ML potential development strategy — directly applicable to Yanhao Deng's MLIP work and Cheng Peng's grain boundary studies. Provides practical guidance on training data curation and validation protocols.
6. Performance-Based Selection of Machine Learning Interatomic Potentials for Solid-State Electrolytes¶
Source: Chemistry of Materials (acs.chemmater.5c02352) · 📅 2026-06-15 · ↗ Open paper
Presents a systematic, performance-based framework for selecting MLIPs in solid-state electrolyte property prediction. Benchmarks multiple MLIP architectures on SSE-relevant properties (ionic conductivity, activation energy, structure relaxation), providing guidance on which models perform best for different SSE material classes. Emphasizes the need for standardized evaluation protocols in the MLIP-for-SSE field.
Relevance to DENG.Group
Directly supports Yanhao Deng's work on ML potentials for solid electrolytes — provides model selection criteria and benchmarking methodology applicable to the group's MLIP development pipeline.
7. Machine learning pipelines for the design of solid-state electrolytes¶
Source: Materials Horizons (d5mh01525a) · 📅 2026-01-20 · ↗ Open paper
Comprehensively surveys ML pipelines for SSE design from data resources and feature engineering through classical models and deep learning architectures. Reviews cutting-edge approaches including graph neural networks, active learning, and generative models for discovering new solid electrolyte compositions with target ionic conductivity and stability properties.
Relevance to DENG.Group
Useful review for the group's ML strategy — provides a landscape overview that can help position the group's ML potential and simulation work relative to competing ML approaches in SSE discovery.
Battery Interfaces & Grain Boundaries¶
8. Machine learning interatomic potential enables interface-level insights into cathode/solid electrolyte adhesion in sodium-ion batteries¶
Source: Journal of Energy Storage (S2352152X26007681) · 📅 2026-06-10 · ↗ Open paper
Demonstrates MLIP-based simulation of cathode/solid electrolyte interfacial adhesion in Na-ion batteries, providing interface-level mechanical and chemical insights. The work showcases how ML potentials capture complex interface phenomena that classical force fields miss, including bond breaking/forming during interface separation and dynamic charge redistribution.
Relevance to DENG.Group
Methodologically relevant to Yanhao Deng's ML potential work and Umang Agarwal's interface studies — demonstrates MLIP application to cathode/electrolyte adhesion that could be translated to Li solid-state systems.
9. Modeling and simulation approaches for solid-state battery interfaces¶
Source: Dalton Transactions (d5dt02804c) · 📅 2026-03-10 · ↗ Open paper
Reviews atomic-scale modeling approaches for interface-controlled phenomena in solid-state batteries, with focus on LiPON–Li metal interfaces. Covers DFT, MD, and MLIP methods for studying interfacial reactions, space charge layers, and mechanical degradation at electrode/electrolyte boundaries.
Relevance to DENG.Group
Directly relevant to Umang Agarwal's heterogeneous interface work and Shoutong Jin's simulations — provides methodological overview for interface modeling that the group can build upon.
10. Electrical imbalances at grain boundaries help explain solid-state battery failures¶
Source: Phys.org / Florida State University · 📅 2026-07-01 · ↗ Open paper
Researchers developed a model explaining how local electrical imbalances at grain boundaries alter ion transport pathways and contribute to battery degradation. The findings suggest that engineering grain boundary chemistry and local charge distributions could mitigate detrimental effects and improve cycling stability in polycrystalline solid electrolytes.
Relevance to DENG.Group
Highly relevant to Cheng Peng's grain boundary research — provides new physical understanding of GB effects on battery performance that could inform simulation targets and material design strategies.
Reviews & Roadmaps¶
11. 2026 roadmap on next-generation solid electrolytes for battery applications¶
Source: Materials Futures / IOP (10.1088/2752-5724/ae5120) · 📅 2026-06-30 · ↗ Open paper
A community roadmap outlining future directions in solid electrolyte research covering oxides, sulfides, halides, and polymer/composite systems. Addresses key challenges in interface engineering, manufacturing scalability, and characterization techniques, with projections for the next 5–10 years of SSB development. Includes contributions from leading groups across KIT and multiple international institutions.
Relevance to DENG.Group
Essential strategic reference for Jerry — identifies emerging research opportunities and positions the group's work (halides, ML potentials, interfaces, grain boundaries) within the broader field trajectory.
12. Accelerating solid-state battery design: predicting ionic conductivity from structure¶
Source: Journal of Materials Chemistry A (d5ta07245j) · 📅 2026-04-15 · ↗ Open paper
Presents a high-throughput computational framework for predicting ionic conductivity in solid-state electrolytes directly from crystal structure, enabling rapid screening across vast chemical spaces. Combines DFT-quality descriptors with ML regression to achieve accurate conductivity predictions orders of magnitude faster than conventional MD simulations.
Relevance to DENG.Group
Relevant to the group's computational screening efforts — methodology could complement Yanhao Deng's ML potential approach for high-throughput SSE discovery.