Research Digest — 2026-07-05¶
Dendrite Growth & Mechanics¶
1. Numerical simulation of key factors affecting dendrite growth in solid-state electrolyte batteries under multi-physical coupling fields¶
Source: Journal of Energy Storage (S2352152X25040770) · 📅 2026-06-20 · ↗ Open paper
A multiphysics numerical simulation study examining how coupled mechanical, electrochemical, and thermal fields jointly control dendrite growth in solid electrolytes. The work systematically varies key parameters (current density, stack pressure, temperature, interfacial defects) and maps their individual and coupled effects on dendrite propagation kinetics. Provides a comprehensive parameter sensitivity analysis relevant to dendrite suppression strategies.
Relevance to DENG.Group
Complements Shoutong Jin's phase field simulations with a multiphysics coupling framework. The parameter sensitivity analysis can guide which boundary conditions matter most in Deng group dendrite models. The coupled electrochemical-mechanical framework aligns with the group's interest in realistic dendrite modeling.
2. Rethinking dendrite growth in solid electrolytes¶
Source: OAE Publishing - Energy Materials (energyz.2026.22) · 📅 2026-06-15 · ↗ Open paper
A perspective that reexamines dendrite growth in solid electrolytes as primarily a fracture process rather than an electrochemical deposition problem. The authors argue that Li plating generates stress at flaws until local stress intensity exceeds the fracture toughness, propagating cracks that Li then fills. This mechanics-first viewpoint has implications for how dendrite suppression should be approached — focusing on mechanical properties rather than just electrochemical stability.
Relevance to DENG.Group
Provides theoretical framing for Shoutong Jin's work and aligns with the Nature paper above on mechanically driven penetration. The fracture-mechanics-first perspective could reframe how the Deng group approaches dendrite modeling — fracture toughness and flaw distribution may be more important inputs than electrochemical parameters.
ML Interatomic Potentials¶
3. Performance-Based Selection of Machine Learning Interatomic Potentials for Solid-State Electrolyte Screening¶
Source: Chemistry of Materials (acs.chemmater.5c02352) · 📅 2026-06-25 · ↗ Open paper
A systematic benchmark study evaluating multiple MLIP architectures (CHGNet, MACE, NequIP, Allegro, etc.) for high-throughput prediction of solid-state electrolyte properties including ionic conductivity, stability, and elastic constants. The work proposes a performance-based selection protocol that accounts for accuracy, computational cost, and transferability across different SSE chemistries (oxides, sulfides, halides).
Relevance to DENG.Group
Core relevance to Yanhao Deng's MLIP work. The benchmarking protocol and architecture comparison directly inform which MLIPs the group should use for different applications. The transferability assessment across SSE chemistries is critical for the group's halide and sulfide electrolyte work. The proposed selection framework could become a standard tool in the group's computational workflow.
4. Advanced solid electrolytes break world record for ionic conductivity¶
Source: University of Maryland Engineering News · 📅 2026-06-15 · ↗ Open paper
A new approach to optimize halide solid electrolytes has achieved record-breaking ionic conductivity levels, surpassing liquid electrolytes for the first time. The UMD team used a combination of aliovalent doping and structural engineering to enhance Li-ion mobility in the halide framework. The material demonstrates both high conductivity and wide electrochemical stability, addressing two key barriers for solid-state batteries simultaneously.
Relevance to DENG.Group
Important benchmark for Yan Li and Mengke Li's halide electrolyte simulations — the record conductivity sets a target for computational predictions and provides experimental validation data. The doping strategy could be explored computationally by the group to understand the atomistic mechanism behind the enhanced conductivity.
Solid Electrolyte Interfaces & Reviews¶
5. Recent advances and remaining challenges of solid-state electrolytes (Comprehensive Review)¶
Source: Current Opinion in Solid State & Materials Science (S0079642525001379) · 📅 2026-06-15 · ↗ Open paper
A systematic review bridging advancements in solid-state electrolyte materials (oxides, sulfides, halides, polymers) with the persistent challenges preventing commercial deployment. The review analyzes structure-property relationships across SSE classes, examines interface engineering strategies, and identifies the most promising pathways for achieving practical all-solid-state batteries. Particular attention is paid to manufacturing scalability and cost considerations.
Relevance to DENG.Group
Broad reference useful for the entire group's literature awareness. The cross-class comparison (oxide vs sulfide vs halide vs polymer) helps validate the group's multi-material research strategy. The identified challenges should inform grant proposals and research direction discussions.
6. Accelerating ion transport in polycrystalline conductors: On pores and grain boundaries¶
Source: Science Advances (sciadv.adt7795) · 📅 2026-06-25 · ↗ Open paper
This Science Advances study reveals how the characteristics and distribution of pores and grain boundaries collectively determine ion conduction in polycrystalline solid electrolytes. The authors show that pore-grain boundary interactions create percolation barriers that dominate macroscopic conductivity. They propose microstructural engineering strategies — controlling pore size, distribution, and GB character — to enhance ion transport beyond current limits.
Relevance to DENG.Group
Directly relevant to Cheng Peng's grain boundary work. The pore-GB interaction framework provides a new dimension beyond isolated GB studies. Cheng Peng should incorporate porosity effects into his GB transport simulations. The microstructural engineering strategies could be validated computationally using the group's existing simulation infrastructure.
7. Open electrolyte database generated via an automated molecular dynamics simulation framework¶
Source: npj Computational Materials (s41524-026-02093-y) · 📅 2026-06-30 · ↗ Open paper
An open database of ~5600 electrolyte formulations generated using a fully automated, high-throughput MD simulation framework. Unlike existing databases that focus on isolated molecular properties, this resource provides electrolyte-level collective properties including ionic conductivity, viscosity, and ion solvation structure. The automation pipeline enables systematic exploration of composition-structure-property relationships across vast chemical spaces.
Relevance to DENG.Group
Valuable resource for Naibing Wu's polymer electrolyte work and the group's broader electrolyte design efforts. The database can serve as training data for ML models predicting electrolyte properties, and the automated simulation framework could be adapted for solid polymer electrolyte screening. The composition-property maps may guide experimental collaborators toward promising formulations.