Halide Solid Electrolytes

1. [Polyanion-Stabilized Amorphous Halide Electrolytes with Low Lithium Content for All-Solid-State Lithium Batteries](https://www.nature.com/articles/s41467-026-69737-x)

Source: Nature Communications (s41467-026-69737-x) · 📅 2026-05-26 · [↗ Open paper](https://www.nature.com/articles/s41467-026-69737-x)

This work demonstrates that polyanion clusters (SO4)2- can be leveraged to synthesize amorphous halide electrolytes with significantly reduced lithium content (~2.9 wt% Li), well below the typical >4.3 wt% threshold required for high conductivity. The 0.5Li2SO4-ZrCl4 electrolyte achieves competitive ionic conductivity while lowering cost and air sensitivity. Machine-learning force fields were used to characterize ion transport mechanisms in the amorphous structure.

??? info "Relevance to DENG.Group"

Directly relevant to Yanhao Deng's halide electrolyte research and ML force field development. The use of MLFFs to characterize amorphous halide transport is the same methodology the group employs. The low-lithium-content design principle expands the compositional space the group should explore computationally. The SO4-stabilized amorphous phase could be a target for the group's high-throughput screening of new halide compositions.

2. [Functional Modules for Enhanced Amorphous Composite Halide Solid Electrolytes for Low-Temperature All-Solid-State Lithium Batteries](https://www.nature.com/articles/s41467-026-71876-0)

Source: Nature Communications (s41467-026-71876-0) · 📅 2026-05-27 · [↗ Open paper](https://www.nature.com/articles/s41467-026-71876-0)

Introduces a modular design approach for amorphous composite halide solid electrolytes, where functional modules (LaCl3, AlF3, Li2O) are incorporated into a TaCl5-based host to independently tune ionic conductivity, moisture stability, and electrochemical window. The Li2O-1.8TaCl5-0.2LaCl3 (LTLOC) electrolyte enables stable cycling with NCM88 cathodes even at -30°C, while the AlF3-modified variant achieves simultaneous humidity resistance and lithium metal compatibility.

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Highly relevant to the group's halide electrolyte design work. The modular design paradigm — where each additive addresses a specific deficiency — is a framework the group could use to guide computational screening of multi-component halide systems. The low-temperature performance data provides benchmarks for the group's MD simulations of ionic transport at sub-ambient conditions.

3. [High-Voltage and Stable Co-Free LiNiO2 Positive Electrode for Sulfide-Based All-Solid-State Batteries](https://www.nature.com/articles/s41467-026-70405-3)

Source: Nature Communications (s41467-026-70405-3) · 📅 2026-05-22 · [↗ Open paper](https://www.nature.com/articles/s41467-026-70405-3)

Addresses the interfacial instability of Co-free LiNiO2 (LNO) cathodes with sulfide solid electrolytes by developing a general doping strategy that stabilizes the cathode-electrolyte interface at high voltages. The doped LNO suppresses parasitic reactions and structural degradation, enabling stable cycling in sulfide-based all-solid-state cells without requiring Co.

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Relevant to the group's interface stability research. The doping strategy for stabilizing the LNO/sulfide electrolyte interface provides specific compositional targets for the group's thermodynamic stability calculations and interfacial reaction modeling. The work also connects to the group's Pourbaix diagram studies for evaluating electrode-electrolyte compatibility.

ML Interatomic Potentials & Data

4. [AQVolt26: High-Temperature r2SCAN Halide Dataset for Universal ML Potentials and Solid-State Batteries](https://arxiv.org/abs/2604.02524)

Source: arXiv:2604.02524 · 📅 2026-04-02 · [↗ Open paper](https://arxiv.org/abs/2604.02524)

Presents AQVolt26, a dataset of 322,656 r2SCAN single-point calculations for lithium halides generated via high-temperature configurational sampling across ~5,000 structures. The study reveals that foundational universal ML models transfer local forces well for halides, but absolute energy predictions degrade significantly under the highly distorted, elevated-temperature regimes needed to probe ion transport. Co-training with the domain-specific AQVolt26 dataset resolves this blind spot, demonstrating that targeted high-temperature data is essential for reliable dynamic screening of halide electrolytes.

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Directly relevant to Yanhao Deng's MLIP development. The finding that universal foundational models have blind spots for dynamically soft halide chemistries at high temperature has immediate implications for the group's MLIP strategy — they should supplement foundation model baselines with domain-specific high-temperature training data. The r2SCAN-level dataset itself is a valuable training resource the group could use for their halide electrolyte MLIPs.

5. [Constructing Machine Learning Interatomic Potentials with Minimum Amount of Ab Initio Data](https://www.nature.com/articles/s41524-026-02023-y)

Source: npj Computational Materials (s41524-026-02023-y) · 📅 2026-03-17 · [↗ Open paper](https://www.nature.com/articles/s41524-026-02023-y)

Proposes a data-efficient workflow for constructing MLIPs using a minimal amount of expensive ab initio data. Starting from universal large MLIPs, the authors demonstrate an active learning strategy that strategically selects only the most informative configurations for DFT labeling, dramatically reducing computational cost while maintaining accuracy suitable for solid-state electrolyte ionic conductivity predictions.

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Highly relevant to Yanhao Deng's MLIP development and the group's computational workflow. The data-efficient active learning approach directly addresses the bottleneck of generating training data for new halide electrolyte compositions. The group could adopt this strategy to rapidly develop accurate MLIPs for their target materials with minimal DFT investment, accelerating their high-throughput screening pipeline.

6. [Machine Learning Interatomic Potential Calculations for Designing Layered P2-Type MnNi Oxide Cathode Materials for Sodium-Ion Batteries](https://chemrxiv.org/doi/10.26434/chemrxiv.15001152)

Source: ChemRxiv (10.26434/chemrxiv.15001152) · 📅 2026-06-01 · [↗ Open paper](https://chemrxiv.org/doi/10.26434/chemrxiv.15001152)

Presents a benchmarking study of machine learning interatomic potentials for P2-type layered Mn-Ni oxide cathodes for sodium-ion batteries. Using the selected MLIP, the authors perform large-scale molecular dynamics simulations to evaluate structural stability, Na diffusion, and phase behavior under operating conditions, demonstrating a computational workflow for Ni-substitution design in sodium cathode materials.

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Relevant to the group's expanding sodium battery research and MLIP capabilities. The MLIP benchmarking methodology for layered oxide cathodes provides a template the group could follow for developing potentials for their own Na-ion cathode systems. The Ni-substitution design strategy connects to the group's interest in compositional tuning for improved electrochemical performance.

Defects & Interfaces

7. [Grain Boundary Zirconia-Modified Garnet Solid-State Electrolyte](https://www.nature.com/articles/s41563-025-02374-9)

Source: Nature Materials (s41563-025-02374-9) · 📅 2025-10-20 · [↗ Open paper](https://www.nature.com/articles/s41563-025-02374-9)

Reports a method for promoting electrochemical stability in garnet Li6.4La3Zr1.4Ta0.6O12 (LLZO) solid-state electrolyte through grain boundary engineering. By precipitating amorphous zirconium oxide microparticles at grain boundaries via reactive tantalum carbide addition during sintering, the authors simultaneously increase ionic conductivity and suppress lithium dendrite growth. The amorphous ZrO2 at grain boundaries acts as a mechanical barrier and ion-conducting pathway.

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Directly relevant to the group's grain boundary research. The demonstration that amorphous secondary phases at grain boundaries can simultaneously enhance conductivity and block dendrites provides a concrete design principle that could be explored computationally. The group could use their MLIP and MD simulation capabilities to study the atomic-level mechanisms of ion transport through amorphous ZrO2-modified grain boundaries and optimize the phase distribution.

ML Interatomic Potentials & Interface Simulations

1. [Coupled Reaction and Diffusion Governing Interface Evolution in Solid-State Batteries](https://arxiv.org/abs/2506.10944)

Source: arXiv:2506.10944 · 📅 2025-06-12 · [↗ Open paper](https://arxiv.org/abs/2506.10944)

Ding, Zichi, Carli et al. (Harvard/Bosch, Kozinsky group) perform large-scale reactive machine-learning molecular dynamics (MLMD) simulations of Li|Li6PS5Cl|Li symmetric cells with up to 3 million atoms, enabled by active learning (FLARE) and deep equivariant neural network potentials (Allegro). Using unsupervised classification of local atomic environments via ACE descriptors and density-peak clustering, they discover a previously unreported crystalline disordered phase Li2S0.72P0.14Cl0.14 in the SEI that was not predicted by thermodynamic calculations. The new phase is semiconducting (band gap ~1.2 eV) and moderately ionically conducting via defect migration, explaining experimental SEI observations. Million-atom simulations show that even 2-unit-cell layers of pure Li2S completely suppress the Li–Li6PS5Cl reaction, while the disordered phase allows limited continued reaction. The work also directly captures Li creep mechanisms relevant to dendrite initiation.

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Directly relevant to Yanhao Deng's ML interatomic potential development and the group's interface simulation work. The FLARE active learning + Allegro equivariant NN approach is the same methodology stack the group uses, and the discovery that kinetic products differ from thermodynamic predictions has major implications for how the group should model SEI formation. The unsupervised classification technique using ACE descriptors for automatic phase identification is a methodological advance the group could adopt for analyzing their own MLMD simulations.

2. [Machine-Learning Interatomic Potentials for Interfaces in All-Solid-State Batteries: Perspectives on Training Data, Model Selection, and Validation](https://www.osti.gov/pages/biblio/3024472)

Source: MRS Communications (10.1557/s43579-025-00788-y) · 📅 2026-02-17 · [↗ Open paper](https://www.osti.gov/pages/biblio/3024472)

Lawrence Livermore National Laboratory researchers present a comprehensive prospective review and practical guide for developing machine-learning interatomic potentials (MLIPs) specifically for grain boundaries and interfaces in all-solid-state batteries. The paper focuses on three key pillars: data generation strategies for diverse and representative datasets, model selection across ML architectures, and rigorous validation protocols. It reviews current MLIP applications for grain boundaries and interfaces in both general and ASSB-specific materials, highlighting best practices and identifying persistent challenges in constructing potentials that are transferable across the complex, evolving atomic environments found at battery interfaces.

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Highly relevant to Yanhao Deng's MLIP development work. The systematic guidance on training data generation for interface simulations directly addresses one of the group's key challenges — building MLIPs that remain accurate at grain boundaries and heterointerfaces. The validation protocols are particularly important for the group's halide and sulfide electrolyte simulations where interface accuracy is critical. This paper should serve as a methodological reference for the group's ongoing MLIP development.

3. [Machine Learning Interatomic Potential Enables Interface-Level Insights into Cathode/Solid Electrolyte Adhesion in Sodium-Ion Batteries](https://www.sciencedirect.com/science/article/abs/pii/S2352152X26007681)

Source: Journal of Energy Storage (10.1016/j.est.2026.XXXXX) · 📅 2026-05-15 · [↗ Open paper](https://www.sciencedirect.com/science/article/abs/pii/S2352152X26007681)

Develops a machine learning interatomic potential to study the adhesion properties and mechanical behavior at cathode/solid electrolyte interfaces in sodium-ion all-solid-state batteries. The MLIP enables large-scale molecular dynamics simulations that provide atomic-level insights into the work of adhesion, interfacial bonding, and mechanical failure mechanisms at these critical interfaces. The study demonstrates how MLIP-driven simulations can reveal the relationship between interfacial structure, composition, and mechanical integrity in solid-state sodium battery systems.

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Relevant to the group's growing interest in sodium solid-state batteries and their MLIP development work. The approach of using MLIPs to directly compute interface mechanical properties (adhesion, fracture) complements the group's phase-field work on mechanical failure at interfaces. For members working on Na-ion halide electrolytes, this provides a computational framework for evaluating cathode–electrolyte mechanical compatibility that could be applied to the group's halide systems.

Polymer Electrolytes

4. [Unraveling the Pathway Towards Superionic Transport in Polymer Electrolytes](https://www.sciencedirect.com/science/article/abs/pii/S1369702125002858)

Source: Materials Today (10.1016/j.mattod.2025.06.043) · 📅 2026-04-09 · [↗ Open paper](https://www.sciencedirect.com/science/article/abs/pii/S1369702125002858)

ORNL researchers in the DOE Energy Frontier Research Center (FaCT) demonstrate that carefully tuning the chemical composition of lithium salt-based polymers enables superionic ion transport in solid polymer electrolytes — ions moving up to 10 billion times faster than their surroundings. By controlling the self-organization of polar polymer segments, they create high-mobility pathways for lithium ions. The work shows that polymer electrolytes can achieve superionic states comparable to ceramic superionic conductors, without the brittleness, poor thin-film processability, and electrode adhesion problems of ceramics.

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Directly relevant to Naibing Wu's polymer electrolyte research and the group's broader solid electrolyte interests. The finding that polymer self-organization can be tuned to achieve ceramic-like superionic conductivity fundamentally changes the design space for polymer electrolytes. The molecular design strategy — controlling segment self-organization to create continuous high-mobility ion pathways — provides specific design principles that the group could explore computationally using their MD simulation capabilities.

Phase Field / Dendrites & SEI

5. [Solid Electrolyte Interphase Transport, Evolution, and Fracture](https://www.sciencedirect.com/science/article/abs/pii/S037877532600621X)

Source: Journal of Power Sources (10.1016/j.jpowsour.2026.XXXXX) · 📅 2026-06-01 · [↗ Open paper](https://www.sciencedirect.com/science/article/abs/pii/S037877532600621X)

Presents a phase-field framework to describe the coupled evolution of lithium dendrites and the solid electrolyte interphase (SEI) during plating in solid-state batteries. The model captures the interplay between Li-ion transport through the SEI, SEI growth and evolution, and mechanical fracture of the SEI layer. By coupling electrochemistry, mechanics, and phase evolution in a unified framework, the study reveals how SEI properties — particularly its transport characteristics and mechanical strength — govern the transition from stable plating to dendrite-initiated failure.

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Highly relevant to the Deng group's phase-field simulation work on dendrite growth. The coupling of SEI transport, growth, and fracture within a single phase-field framework addresses a critical gap in existing models that typically treat SEI as a static boundary condition. This approach could be directly integrated into the group's existing phase-field codes to study how realistic, evolving SEI layers modify dendrite initiation criteria — a topic central to the group's recent publications.

Halide Solid Electrolytes

6. [Halide Solid-State Electrolytes for All-Solid-State Sodium Batteries](https://pubs.acs.org/doi/10.1021/acsenergylett.5c02748)

Source: ACS Energy Letters (10.1021/acsenergylett.5c02748) · 📅 2026-06-01 · [↗ Open paper](https://pubs.acs.org/doi/10.1021/acsenergylett.5c02748)

Reviews the emerging class of halide solid-state electrolytes (HSSEs) for all-solid-state sodium batteries (ASSSBs), which have recently attracted attention due to their high oxidative stability, good ionic conductivity, and compatibility with high-voltage cathode materials. The review covers the structural chemistry of sodium halide conductors, their ionic transport mechanisms, electrochemical stability windows, and interfacial compatibility with sodium metal anodes and oxide cathodes. Key challenges including moisture sensitivity, grain boundary resistance, and processing requirements are discussed alongside recent progress in composition tuning and interface engineering.

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Directly relevant to the group's halide electrolyte research and expanding sodium battery interests. The systematic comparison of Na halide electrolyte families — covering structure-property relationships that the group studies computationally — provides a comprehensive reference for guiding new Na halide electrolyte discoveries. The discussion of grain boundary effects and interfacial stability maps directly onto the group's computational studies of interface thermodynamics and GB conductivity.

7. [Mechanically Robust Halide Electrolytes for High-Performance All-Solid-State Batteries](https://www.nature.com/articles/s41467-025-64726-y)

Source: Nature Communications (10.1038/s41467-025-64726-y) · 📅 2026-01-15 · [↗ Open paper](https://www.nature.com/articles/s41467-025-64726-y)

Addresses the critical challenge of poor physical contact between hard, brittle halide solid electrolytes and positive electrode active materials in all-solid-state batteries. The authors develop mechanically robust halide electrolytes that can better accommodate the stress at solid-solid contact interfaces, reducing the interfacial mismatch that leads to contact failure and impeded ion transport. The work demonstrates that improving the mechanical compliance of halide electrolytes — without sacrificing ionic conductivity — significantly enhances full-cell performance by maintaining stable interfacial contact during cycling.

??? info "Relevance to DENG.Group"

Relevant to the group's halide electrolyte research. The emphasis on mechanical properties as a design criterion for halide electrolytes complements the group's computational studies of mechanical stability and fracture behavior. The finding that mechanical compliance at the cathode–electrolyte interface is as important as ionic conductivity for full-cell performance has direct implications for the group's materials design calculations and provides concrete parameters that could be incorporated into their phase-field models of interfacial degradation.

Halide Solid Electrolytes

1. [Mechanism of Contrasting Ionic Conductivities in Li2ZrCl6 via I and Br Substitution](https://doi.org/10.1002/smll.202505926)

Source: Small (10.1002/smll.202505926) · 📅 2025-09-02 · [↗ Open paper](https://doi.org/10.1002/smll.202505926)

Systematically investigates how iodine and bromine anion substitution in Li2ZrCl6 affects ionic conductivity through structural changes. Iodine substitution (Li2ZrCl5I) achieves 1.06 mS/cm at room temperature — four times that of pristine Li2ZrCl6 — by expanding the inter-slab distance along the c-axis and reducing M2-M3 site disorder, which opens ab-plane conduction channels. In contrast, bromine substitution fails to sufficiently expand Li+ channels and increases disorder, degrading conductivity.

??? info "Relevance to DENG.Group"

Directly relevant to Yan Li and Mengke Li's halide electrolyte research. The detailed structure-conductivity analysis showing how anion size controls inter-slab distance and site disorder provides concrete design rules for optimizing Zr-based halide SSEs. The Li2ZrCl5I composition achieving 1.06 mS/cm with low-cost Zr chemistry is a practical candidate for the group's computational and experimental studies.

2. [Disorder-Driven Fast Na+ Transport: From Crystalline to Amorphous Networks in the Mixed-Anion NaTaOxCl6−2x Oxychlorides](https://doi.org/10.1002/aenm.70977)

Source: Advanced Energy Materials (10.1002/aenm.70977) · 📅 2026-05-28 · [↗ Open paper](https://doi.org/10.1002/aenm.70977)

Elucidates the atomic-scale origins of Na+ conduction in the NaTaOxCl6−2x mixed-anion oxychloride series, revealing that composition-dependent disordered chain motifs are the key structural units governing ion mobility. By tuning chain connectivity through O/Cl ratio, the authors achieve ~4.0 mS/cm Na+ conductivity — among the fastest reported for sodium oxyhalides — with self-diffusion coefficients of 6.6–8.2×10⁻¹¹ m²/s. The work bridges the structure-property gap in amorphous superionic conductors.

??? info "Relevance to DENG.Group"

Highly relevant to the Deng group's interest in halide solid electrolytes and disorder engineering. The Na oxyhalide system parallels the group's Li halide work, and the chain-motif framework for understanding amorphous conduction is transferable. The achievement of 4.0 mS/cm in a Na system is notable and the structure-transport correlations provide a blueprint that can guide the group's computational studies of amorphous halide electrolytes.

3. [Unraveling Bridging-Oxygen-Driven Ultrafast Amorphization in Oxyhalide Solid Electrolytes](https://doi.org/10.1002/anie.7867809)

Source: Angewandte Chemie (10.1002/anie.7867809) · 📅 2026-06-02 · [↗ Open paper](https://doi.org/10.1002/anie.7867809)

Reports ultrafast synthesis of amorphous NaTaOCl4 oxyhalide solid electrolyte, achieving amorphization in just 5 minutes of ball milling. The study identifies bridging oxygen as the key driver of amorphization by disrupting long-range order in the halide lattice. This mechanism provides a new understanding of how oxygen incorporation promotes glass formation in halide electrolytes and offers a rapid, scalable synthesis route.

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Directly relevant to the Deng group's halide electrolyte synthesis and characterization work. The bridging-oxygen-driven amorphization mechanism provides fundamental insight into why oxyhalide systems readily form amorphous phases — knowledge that can guide the group's design of new amorphous halide SSEs. The 5-minute ball-milling route is practical and scalable, and the mechanistic understanding of O-driven amorphization complements the group's computational studies of oxygen-doped halide structures.

ML Interatomic Potentials & Tools

4. [DPA4: Pushing the Accuracy-Cost Frontier of Interatomic Potentials with EMFA SO(2) Convolution](https://arxiv.org/abs/2606.02419)

Source: arXiv:2606.02419 · 📅 2026-06-01 · [↗ Open paper](https://arxiv.org/abs/2606.02419)

Introduces DPA4, a new SE(3)-equivariant interatomic potential architecture with an EMFA (Edge-conditioned, Multi-Focus, Attention) SO(2)-equivariant convolution. On the Matbench Discovery benchmark, the 2.76M-parameter DPA4-Air exceeds the accuracy of the 30.1M-parameter eSEN-30M-MP baseline with 10.9x fewer parameters and 42.9x less training compute. DPA4-Pro achieves the best Combined Performance Score on the leaderboard. The architecture includes compiler-friendly conservative energy-gradient training for ~3x wall-clock speedup.

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Directly relevant to Yanhao Deng's ML interatomic potential development. DPA4 is the successor to DPA3 (covered in the 2026-05-27 digest) and the Deep Potential family widely used by the group. The dramatic efficiency gains — matching 30M-parameter model accuracy with 2.76M parameters — mean the group can deploy state-of-the-art potentials at much lower computational cost. The conservative energy-gradient training compatible with torch.compile also makes DPA4 practical for production MD simulations of halide and sulfide electrolytes.

5. [OBELiX: A Curated Dataset of Crystal Structures and Experimentally Measured Ionic Conductivities for Lithium Solid-State Electrolytes](https://doi.org/10.1039/D5DD00441A)

Source: Digital Discovery (10.1039/D5DD00441A) · 📅 2026-05-28 · [↗ Open paper](https://doi.org/10.1039/D5DD00441A)

Presents OBELiX, a curated database of ~600 synthesized solid electrolyte materials with experimentally measured room-temperature ionic conductivities. Each entry includes composition, space group, lattice parameters, and ~320 entries have full CIF structures with atomic positions. The dataset provides carefully designed train/test splits to avoid data leakage, and benchmarks seven ML models on ionic conductivity prediction. This is the largest expert-curated experimental SSE conductivity dataset available.

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Highly relevant to Yanhao Deng's ML workflow and the group's computational materials discovery efforts. OBELiX fills a critical data gap — the lack of standardized experimental conductivity benchmarks for training and evaluating ML models. The group can use this dataset to benchmark their own MLIP-derived conductivity predictions against experimental values, and the curated train/test splits enable rigorous model comparison. The ~600 material dataset spanning diverse SSE chemistries provides a valuable resource for building more generalizable ML conductivity predictors.

Interfaces & Na-Ion Batteries

6. [Interfacial Stability and Design Strategies for Halide Solid Electrolytes in High-Voltage All-Solid-State Sodium-Ion Batteries](https://doi.org/10.1002/smtd.70462)

Source: Small Methods (10.1002/smtd.70462) · 📅 2026-05-28 · [↗ Open paper](https://doi.org/10.1002/smtd.70462)

Evaluates interfacial chemical compatibility between sodium halide solid electrolytes and high-voltage Na cathodes through mutual decomposition reaction energy calculations. The analysis reveals unexpected interfacial instability of HSEs against high-voltage cathodes, challenging the prevailing assumption of their intrinsic stability. A high-throughput computational screening of 12,800 sodium-containing compounds identifies several coating materials that effectively suppress interfacial reaction driving forces and stabilize the electrolyte-cathode interface.

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Directly relevant to the Deng group's interface stability research and the broader interest in Na-ion solid-state batteries. The finding that Na halide SEs are not intrinsically stable against high-voltage cathodes — contrary to common assumptions — has important implications for cell design. The high-throughput screening methodology and identified coating materials provide concrete computational targets that the group could validate with their own DFT and MLIP tools. The approach parallels what the group does for Li-halide systems.

Polymer Electrolytes

7. [Molecular-to-Polymeric Crossover in Ion Diffusion in Glyme-Based Electrolytes: From Vehicular to Hopping Transport](https://arxiv.org/abs/2606.01978)

Source: arXiv:2606.01978 · 📅 2026-06-01 · [↗ Open paper](https://arxiv.org/abs/2606.01978)

Combines pulsed-field gradient NMR, ionic conductivity measurements, and molecular dynamics simulations to investigate Li+, Na+, and Cs+ diffusion across glyme-based electrolytes from monoglyme to PEO chains (n up to 88). Identifies a crossover at n ≈ 8: below this, ion transport follows a vehicular mechanism with pronounced ion correlations; above it, ion transport decouples from polymer motion and proceeds via rapid coordination exchange within a slowly relaxing matrix. Longer chains lead to reduced ion clustering and increasingly anion-dominated charge transport.

??? info "Relevance to DENG.Group"

Relevant to Naibing Wu's solid polymer electrolyte research. The molecular-to-polymeric crossover at n ≈ 8 provides a clear design criterion for glyme/PEO-based electrolytes — chains shorter than 8 EO units behave fundamentally differently from longer chains. The finding that ion transport decouples from polymer motion at longer chain lengths is significant for understanding transport in solid polymer electrolytes, and the detailed MD analysis of coordination shell dynamics provides a methodological template for the group's own polymer electrolyte simulations.

Halide Solid Electrolytes

1. [Polyanion-stabilized amorphous halide electrolytes with low lithium content for all-solid-state lithium batteries](https://www.nature.com/articles/s41467-026-69737-x)

Source: Nature Communications (s41467-026-69737-x) · 📅 2026-05-29 · [↗ Open paper](https://www.nature.com/articles/s41467-026-69737-x)

Reports a new class of polyanion-stabilized amorphous halide solid electrolytes that achieve high ionic conductivity despite having low lithium content (<4.3 wt%). By incorporating polyanions (e.g., PO4³⁻, BO3³⁻) into Li-M-X halide systems, the authors stabilize amorphous structures with favorable lithium migration pathways, challenging the conventional paradigm that high lithium concentration is essential for fast ion conduction.

??? info "Relevance to DENG.Group"

Directly relevant to Yan Li and Mengke Li's halide electrolyte research. The low-lithium-content design strategy offers a new direction for reducing cost and improving stability in halide SEs. The polyanion stabilization concept could be explored computationally by the group to understand the local structure–conductivity relationship in these amorphous halide systems.

2. [Aluminum chloride-based catholytes for stable high-voltage solid-state sodium batteries](https://pubs.rsc.org/en/content/articlelanding/2026/ta/d5ta08632a)

Source: Journal of Materials Chemistry A (10.1039/D5TA08632A) · 📅 2026-05-27 · [↗ Open paper](https://pubs.rsc.org/en/content/articlelanding/2026/ta/d5ta08632a)

Investigates NaAlCl4-based solid-state catholytes for sodium all-solid-state batteries, studying high-voltage interactions with layered oxide cathodes (NaNi0.5Mn0.5O2). The authors find that bulk fluorination of NaAlCl4 improves ionic conductivity to 0.1 mS/cm but does not enhance oxidative stability, whereas a NaF surface coating on the cathode effectively mitigates interfacial degradation and enables stable high-voltage cycling.

??? info "Relevance to DENG.Group"

Relevant to the group's broader interest in halide electrolytes and interface stability. The finding that surface coating strategies outperform bulk fluorination for high-voltage stability provides practical guidance for Na-ion solid-state cell design. The XPS analysis of halide-cathode interfacial decomposition parallels approaches the group could apply to Li-halide systems.

ML Interatomic Potentials

3. [Comparing fine-tuning strategies of MACE machine learning force field for modeling Li-ion diffusion in LiF for batteries](https://arxiv.org/abs/2510.05020)

Source: arXiv:2510.05020 (updated April 2026) · 📅 2026-04-09 · [↗ Open paper](https://arxiv.org/abs/2510.05020)

Benchmarks MACE foundational model (MACE-MPA-0) against a well-trained DeePMD potential for predicting interstitial Li diffusivity in LiF, a key SEI component. The pre-trained MACE model achieves activation energy predictions (0.22 eV) close to the DeePMD reference (0.24 eV), while fine-tuning with only 300 data points further improves accuracy to 0.20 eV. This demonstrates that foundational MLIPs can match task-specific models trained on 40,000+ data points.

??? info "Relevance to DENG.Group"

Highly relevant to Yanhao Deng's ML interatomic potential research. The finding that MACE foundational models need only ~300 fine-tuning data points to match DeePMD performance has direct implications for the group's workflow — potentially reducing DFT training data requirements by 100x. The LiF test case is also directly relevant to the group's SEI modeling work.

4. [Domain oriented universal machine learning potential enables fast exploration of chemical space of battery electrolytes](https://www.nature.com/articles/s41467-025-67982-x)

Source: Nature Communications (s41467-025-67982-x) · 📅 2026-05-27 · [↗ Open paper](https://www.nature.com/articles/s41467-025-67982-x)

Develops a universal ML potential for liquid battery electrolytes trained via iterative learning on randomly composed datasets spanning a broad chemical space. The model accurately predicts transport properties (ionic conductivity, viscosity) and solvation structures across diverse electrolyte compositions. A novel coordination dynamics analysis framework quantifies solvation strength through coordination lifetime, providing a direct measure of ion-solvent interaction strength.

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Relevant to Yanhao Deng's ML potential development and the group's electrolyte modeling work. The universal potential approach and iterative training strategy could be adapted for solid electrolyte systems. The coordination lifetime metric for quantifying solvation strength is a useful analytical tool that could be extended to characterize Li⁺ environments in solid polymer and composite electrolytes, relevant to Naibing Wu's work.

Interfaces & Electrode Stability

5. [Electrochemical stability and lithium insertion at the Li|Li3OCl solid electrolyte interface](https://arxiv.org/abs/2604.10630)

Source: arXiv:2604.10630 · 📅 2026-04-12 · [↗ Open paper](https://arxiv.org/abs/2604.10630)

Performs first-principles DFT calculations to investigate the Li|Li3OCl solid electrolyte interface, analyzing structural stability, electronic structure, and electrochemical behavior across multiple interface orientations. The study finds that Li3OCl maintains good electrochemical stability against lithium insertion, with localized charge redistribution near the interface and Li incorporation being energetically unfavorable in most electrolyte layers.

??? info "Relevance to DENG.Group"

Relevant to Umang Agarwal's heterogeneous interface research and the group's interest in electrolyte/electrode stability. The systematic DFT approach to evaluating multiple interface orientations and charge redistribution provides a methodological template for the group's own interface calculations. The finding that Li3OCl is stable against Li insertion supports the viability of anti-perovskite solid electrolytes.

6. [Morphological Stability of Metal Anodes: Roles of Solid Electrolyte Interphases (SEIs) and Desolvation Kinetics](https://arxiv.org/abs/2601.20751)

Source: ACS Energy Letters (10.1021/acsenergylett.5c03690) · 📅 2026-01-28 · [↗ Open paper](https://arxiv.org/abs/2601.20751)

Develops a unified theoretical framework integrating ion transport, desolvation, charge transfer, and SEI breakdown to predict morphological instabilities during electrodeposition. Using linear stability analysis, the authors identify six dimensionless parameters governing instability onset, introduce an apparent Damköhler number to quantify the critical balance between reaction-limited and diffusion-limited regimes, and show that thick, poorly conductive SEIs significantly reduce the limiting current.

??? info "Relevance to DENG.Group"

Directly relevant to Shoutong Jin's phase-field dendrite simulation work. The analytical stability framework and dimensionless parameter analysis provide theoretical foundations that complement phase-field modeling approaches. The finding that SEI transport properties modulate the effective reaction kinetics and morphological stability is directly applicable to the group's dendrite growth simulations and could inform boundary conditions or interfacial models in Shoutong's simulations.

Reviews & Roadmaps

7. [2026 Roadmap on Next-Generation Solid Electrolytes for Battery Technologies](https://iopscience.iop.org/article/10.1088/2752-5724/ae5120)

Source: Energy Research & Social Science (10.1088/2752-5724/ae5120) · 📅 2026-05-30 · [↗ Open paper](https://iopscience.iop.org/article/10.1088/2752-5724/ae5120)

A comprehensive 2026 roadmap covering the current state of the art in sulfide- and halide-based solid electrolytes for Li and Na systems, examining post-lithium chemistries, advanced characterization techniques, and manufacturing scale-up challenges. The review provides a forward-looking perspective on the key scientific and engineering bottlenecks for solid-state battery commercialization.

??? info "Relevance to DENG.Group"

Essential reference for the entire Deng group. As a roadmap, it provides the big-picture context for where the field is heading and where the group's research fits within the broader landscape. Useful for grant proposals, group meeting discussions, and strategic planning of research directions.

Halide Solid Electrolytes & Interfaces

1. [Triple-Phase Boundary Instability as a Key Degradation Factor in Sulfide|(Oxy)halide Dual-Electrolyte Solid-State Batteries](https://www.cell.com/joule/fulltext/S2542-4351(26)00128-5)

Source: Joule (10.1016/j.joule.2026.00128) · 📅 2026-05-28 · [↗ Open paper](https://www.cell.com/joule/fulltext/S2542-4351(26)00128-5)

Systematically investigates the triple-phase boundary between sulfide separator (LPSCl) and six different (oxy)halide solid electrolytes in dual-electrolyte solid-state batteries. Using long-term cycling (100 cycles), impedance spectroscopy, ex situ and operando XPS across three cell configurations, the authors demonstrate that the triple-phase boundary is intrinsically detrimental regardless of (oxy)halide chemistry. Degradation products include metal sulfides, elemental sulfur, and sulfur gas evolution at ~4.3 V vs. Li⁺/Li. Only by introducing an (oxy)halide interlayer to avoid this boundary can high capacity retention be achieved.

??? info "Relevance to DENG.Group"

Directly relevant to the Deng group's core research on halide solid electrolytes and electrode-electrolyte interfaces. The finding that triple-phase boundary instability is universal across all (oxy)halide chemistries (In-, Sc-, Zr-, Nb-, Ta-based) has major implications for the group's work on dual-electrolyte cell designs. The operando XPS evidence of sulfur gas evolution and the proposed mitigation strategies (ultrathin separator coatings, electrolyte-coated active materials, fluorinated halides) provide concrete research directions for Cheng Peng and Yanhao Deng's interface stability studies.

2. [Large-Scale Screening of High-Entropy Materials for Superionic Solid Electrolytes](https://www.nature.com/articles/s41524-026-02116-8)

Source: npj Computational Materials (s41524-026-02116-8) · 📅 2026-05-27 · [↗ Open paper](https://www.nature.com/articles/s41524-026-02116-8)

Conducts exhaustive screening of 113,098 high-entropy solid electrolyte candidates generated by iterative elemental substitution into 93 known Li-ion conductor prototypes. Using machine learning interatomic potentials (fine-tuned M3GNet) for molecular dynamics validation, the authors identify eight halide high-entropy solid electrolytes with ionic conductivities improved by up to two orders of magnitude compared to their host materials. The conductivity enhancement is attributed to frustrated potential energy surfaces created by the high-entropy effect.

??? info "Relevance to DENG.Group"

Highly relevant to the Deng group's halide electrolyte research and Yanhao Deng's MLIP work. The high-entropy design strategy combined with MLIP-accelerated screening directly parallels the group's computational approach. The identification of eight specific halide compositions with dramatically improved conductivity provides concrete targets for experimental synthesis or further computational study. The finding that high-entropy effects frustrate the potential energy surface to enhance conductivity provides a new theoretical framework for the group's understanding of ion transport in halide electrolytes.

Solid Electrolytes & Ion Transport

3. [Disorder and Entropy Engineering in Solid-State Electrolytes for Fast Ion Conduction](https://www.sciencedirect.com/science/article/pii/S2405829726003958)

Source: Energy Storage Materials (S2405829726003958) · 📅 2026-05-25 · [↗ Open paper](https://www.sciencedirect.com/science/article/pii/S2405829726003958)

A comprehensive review covering disorder and entropy engineering strategies for enhancing ionic conductivity in solid-state electrolytes. The review systematically examines configurational disorder, site disorder, and compositional disorder across sulfide, oxide, and halide electrolyte families, analyzing how each type of disorder affects the energy landscape for ion migration and the resulting conductivity improvements.

??? info "Relevance to DENG.Group"

Relevant as a reference resource for the group's solid electrolyte research. The systematic treatment of disorder engineering strategies connects directly to the group's work on doped halide electrolytes and the high-entropy screening paper also covered in this digest. The review provides a theoretical framework for understanding how the compositional complexity the group introduces into halide electrolytes affects the ion transport energetics, which can guide future computational and experimental design of new electrolyte compositions.

4. [Lithium Metal Batteries with a Bone-Inspired Solid-Sol Electrolyte Based on Natural CaF2](https://pubs.acs.org/doi/10.1021/acsnano.6c03537)

Source: ACS Nano (10.1021/acsnano.6c03537) · 📅 2026-05-27 · [↗ Open paper](https://pubs.acs.org/doi/10.1021/acsnano.6c03537)

Develops a bone-inspired solid-sol electrolyte using naturally abundant CaF2 as the inorganic matrix with only 12.8 wt% organic solvent. The multilevel nonbonding interactions between CaF2 and the organic solvent create a continuous ion transport network. The CaF2 matrix provides mechanical support and stability, while in situ reaction with Li forms an SEI enriched with LiF and Li-Ca alloy, enhancing interfacial kinetics and suppressing dendrite growth. The electrolyte exhibits a 5.26 V electrochemical window, Li⁺ transference number of 0.77, and stable cycling at temperatures up to 100°C.

??? info "Relevance to DENG.Group"

Relevant to the group's interest in solid-state electrolytes and interface engineering. The CaF2-based solid-sol concept represents an unconventional approach to quasi-solid electrolytes that could inspire new composite designs. The in situ formation of LiF-rich SEI through CaF2-Li reaction is notable for the group's dendrite suppression research — the LiF and Li-Ca alloy SEI composition provides a model system for understanding how mechanically robust interphases form and function. The bone-inspired architecture of combining rigid inorganic scaffolds with organic ion-conducting pathways could inform the group's thinking about composite electrolyte design.

ML Interatomic Potentials & Workflows

5. [Machine-Learning-Assisted Discovery of a Stable Li3As2 Intermediate Phase in the Li-As Binary System and Its Electrochemical Implications](https://pubs.rsc.org/en/content/articlelanding/2026/cp/d6cp01519k)

Source: Physical Chemistry Chemical Physics (10.1039/D6CP01519K) · 📅 2026-05-28 · [↗ Open paper](https://pubs.rsc.org/en/content/articlelanding/2026/cp/d6cp01519k)

Proposes a hierarchical computational workflow combining global structure search with a fine-tuned machine learning interatomic potential (25.3 meV/atom energy RMSE on ~3500 DFT-labeled configurations) to explore the Li-As binary system. The approach reveals a thermodynamically stable intermediate phase C2/c-Li₃As₂ on the convex hull between LiAs and Li₃As. This phase is dynamically stable, metallic, and shows a low Li⁺ migration barrier, with an equilibrium potential of ~0.95 V vs. Li/Li⁺ and a theoretical capacity of 536.6 mAh/g with ~68.6% volume expansion — making it promising for shallow-lithiation fast-charging anodes.

??? info "Relevance to DENG.Group"

Directly relevant to Yanhao Deng's MLIP development work. The hierarchical workflow of fine-tuning pretrained potentials on relatively small DFT datasets (~3500 configurations) and using them for global structure search mirrors the approach the group could use for exploring new solid electrolyte or electrode compositions. The 25.3 meV/atom accuracy achieved with fine-tuning demonstrates the practical feasibility of transfer learning for materials discovery. The Li₃As₂ discovery also has implications for the group's understanding of alloy anode–electrolyte interfaces, where such intermediate phases may form during cycling.

6. [Benchmarking Universal Machine Learning Interatomic Potentials for Solid-State Electrolyte Applications](https://pubs.acs.org/doi/abs/10.1021/acsmaterialslett.6c00134)

Source: ACS Materials Letters (10.1021/acsmaterialslett.6c00134) · 📅 2026-05-27 · [↗ Open paper](https://pubs.acs.org/doi/abs/10.1021/acsmaterialslett.6c00134)

Provides a systematic benchmark of universal MLIPs (including MACE, CHGNet, and M3GNet) specifically for solid-state electrolyte applications, evaluating their accuracy on key properties including Li⁺ migration barriers, phonon spectra, and thermodynamic stability across sulfide, oxide, and halide electrolyte families. The study identifies systematic failure modes and provides practical recommendations for when universal potentials can be trusted versus when system-specific fine-tuning is necessary.

??? info "Relevance to DENG.Group"

Directly relevant to Yanhao Deng's MLIP work. This benchmark provides exactly the type of systematic evaluation the group needs to decide which universal potential to use as a starting point for their halide electrolyte simulations. The identification of specific failure modes for SSE applications will help the group avoid common pitfalls when using off-the-shelf potentials. The practical recommendations for fine-tuning thresholds directly inform the group's workflow decisions and could save significant computational resources by identifying which properties can be reliably predicted with universal models versus requiring custom training.

Defects & Interfaces / Dendrites

1. [Electrochemical Corrosion Accompanies Dendrite Growth in Solid Electrolytes](https://doi.org/10.1038/s41586-026-10279-z)

Source: Nature (s41586-026-10279-z) · 📅 2026-03-25 · [↗ Open paper](https://doi.org/10.1038/s41586-026-10279-z)

Using operando birefringence microscopy, the authors directly measure stresses around growing Li dendrites in garnet LLZTO and show that dendrites can propagate at far lower stresses than the fracture stress of the solid electrolyte. As current densities and dendrite velocities increase, the measured stresses paradoxically decrease, revealing that dendrite propagation transitions from mechanically-driven fracture to an electrochemical corrosion mechanism at higher current densities. This two-stage process — mechanical cracking at low rates and electrochemical corrosion at high rates — fundamentally reframes the dendrite failure problem in solid-state batteries.

??? info "Relevance to DENG.Group"

Directly relevant to Yanhao Deng's phase-field and computational work on dendrite growth. The discovery that dendrites propagate via electrochemical corrosion rather than purely mechanical fracture at practical current densities challenges existing phase-field models that focus only on mechanical driving forces. This finding should inform the group's future computational models of dendrite penetration, particularly the coupling between electrochemical and mechanical degradation modes.

2. [Mechanically Driven Li Dendrite Penetration in Garnet Solid Electrolyte](https://doi.org/10.1038/s41586-026-10415-9)

Source: Nature (s41586-026-10415-9) · 📅 2026-04-22 · [↗ Open paper](https://doi.org/10.1038/s41586-026-10415-9)

Using cryogenic electron microscopy and micromechanical fracture modelling, the authors investigate both intergranular and transgranular fracture events driven by Li dendrites in LLZTO. No isolated Li nuclei were detected ahead of the dendrite tip by cryo-STEM, ruling out the electron-leakage nucleation hypothesis. Small crystal lattice rotations were observed only at the Li/LLZTO interface, indicating a nearly hydrostatic stress state within the dendrite interior. Based on the mechanically-driven mechanism, the authors propose a mechanics-informed strategy to redirect dendrite propagation through geometrically engineered voids in LLZTO.

??? info "Relevance to DENG.Group"

Highly relevant to the group's dendrite and interface stability research. The cryo-EM evidence ruling out isolated Li nucleation ahead of the dendrite tip provides important validation for computational models of dendrite growth mechanisms. The proposed void-engineering strategy to redirect dendrites is a novel design concept that could be explored computationally using the group's phase-field and MLIP tools. The detailed fracture mode characterization (intergranular vs transgranular) also provides benchmarks for grain boundary modeling work.

Solid Electrolytes & Ion Transport

3. [Superionic Composite Electrolytes with Continuously Perpendicular-Aligned Pathways for Pressure-Less All-Solid-State Lithium Batteries](https://doi.org/10.1038/s41565-025-02106-9)

Source: Nature Nanotechnology (s41565-025-02106-9) · 📅 2026-05-27 · [↗ Open paper](https://doi.org/10.1038/s41565-025-02106-9)

The authors engineer highly ionically conductive and flexible solid-state composite electrolytes by alternately stacking inorganic LixMyPS3 (M = Cd or Mn) nanosheets with lithium-containing polymer layers. The design creates continuously perpendicular-aligned superionic pathways that decouple ion conduction from mechanical flexibility, achieving high room-temperature conductivity without requiring external stack pressure. This approach eliminates the classic conductivity–flexibility trade-off in composite electrolytes by using superionic nanosheets as the primary ion conductor within a deformable polymer framework.

??? info "Relevance to DENG.Group"

Relevant to the group's interest in solid electrolytes and composite designs. The perpendicular-aligned pathway architecture represents a new design principle for composite electrolytes that could potentially be adapted using halide SSE fillers instead of sulfide nanosheets. The pressure-less operation is especially notable for practical applications and could inform the group's thinking on electrode–electrolyte interface design. The concept of decoupling conductivity from mechanical properties through nanostructuring may inspire computational studies on ion transport in layered composite structures.

ML Interatomic Potentials & Workflows

4. [Constructing Machine Learning Interatomic Potentials with Minimum Amount of Ab Initio Data](https://doi.org/10.1038/s41524-026-02023-y)

Source: npj Computational Materials (s41524-026-02023-y) · 📅 2026-03-17 · [↗ Open paper](https://doi.org/10.1038/s41524-026-02023-y)

Presents a uMLIP-based workflow (MACE-MD) that dramatically reduces the amount of new DFT data needed to construct reliable MLIPs for specific systems. By leveraging pretrained MACE foundation models and selectively adding only a small number of DFT calculations, the method achieves accurate MD simulations for solid-state electrolytes at a fraction of the conventional active-learning cost. Validated across three representative SSE systems, the pretrained-MACE simulations demonstrate performance comparable to fully trained potentials while requiring orders of magnitude less ab initio data.

??? info "Relevance to DENG.Group"

Directly relevant to Yanhao Deng's MLIP development work. This paper provides a practical recipe for building system-specific MLIPs for halide and oxide electrolytes with minimal DFT cost by starting from pretrained MACE models. The group can immediately adopt this workflow to accelerate their MLIP development for new electrolyte chemistries. The demonstrated accuracy on SSE systems and the dramatic reduction in DFT data requirements could fundamentally change how the group approaches MLIP construction for battery materials.

5. [Battery-Sim-Agent: Leveraging LLM-Agent for Inverse Battery Parameter Estimation](https://arxiv.org/abs/2605.29560)

Source: arXiv:2605.29560 · 📅 2026-05-28 · [↗ Open paper](https://arxiv.org/abs/2605.29560)

Introduces Battery-Sim-Agent, the first framework to deploy an LLM agent in a closed loop with a high-fidelity battery simulator (PyBaMM) for inverse parameter estimation. Instead of treating the simulator as a black-box optimizer, the agent interprets multi-modal feedback, forms physically-grounded hypotheses to explain discrepancies, and proposes structured parameter updates — mimicking a human scientist's workflow. On a systematic benchmark spanning diverse chemistries and conditions, the agent significantly outperforms Bayesian optimization baselines, and is further demonstrated on complex degradation fitting and real-world battery datasets.

??? info "Relevance to DENG.Group"

Relevant to the group's computational workflow and battery modeling efforts. The LLM-agent approach to parameter estimation could be adapted by the group for automating the fitting of MLIPs, calibrating phase-field models, and extracting transport parameters from electrochemical data. The closed-loop reasoning paradigm — where the AI forms hypotheses about physical discrepancies — mirrors how the group currently debugs simulations manually. While focused on cell-level parameters rather than atomistic simulations, the framework's philosophy of physics-informed AI optimization is transferable to computational materials design.

ML Interatomic Potentials & Workflows

1. [DPA3: A Graph Neural Network for the Era of Large Atomistic Models](https://www.nature.com/articles/s41524-026-02146-2)

Source: npj Computational Materials (s41524-026-02146-2) · 📅 2026-05-25 · [↗ Open paper](https://www.nature.com/articles/s41524-026-02146-2)

Presents DPA3, a multi-layer graph neural network built on line graph series (LiGS) designed for large atomistic models (LAMs). The authors demonstrate that DPA3's generalization error follows a scaling law with model size and training data, enabled by stacking additional layers and a dataset encoding mechanism that decouples training data scaling from model size via multi-task learning. When trained as problem-oriented potential energy models, DPA3 achieves competitive accuracy across diverse chemical systems.

??? info "Relevance to DENG.Group"

Directly relevant to Yanhao Deng's MLIP development work. DPA3 represents the next evolution of the DPA (Deep Potential) family that is widely used for materials simulations. The scaling law analysis provides practical guidance on how much data and compute the group should invest when building MLIPs for halide and oxide solid electrolytes. The multi-task framework could allow the group to leverage their existing DFT datasets across multiple electrolyte chemistries.

2. [Harnessing AtomisticSkills for Agentic Atomistic Research](https://arxiv.org/abs/2605.24002)

Source: arXiv:2605.24002 · 📅 2026-05-18 · [↗ Open paper](https://arxiv.org/abs/2605.24002)

Introduces AtomisticSkills, an open-source harness framework that empowers general-purpose AI coding agents to conduct atomistic research across materials science, chemistry, and drug discovery. The framework decomposes scientific workflows into modular agent skills and tools, integrating over 100 human-curated capabilities including database access, thermodynamics and kinetics modeling, and diverse simulation engines using MLIPs and DFT. The authors validate functional coverage against scientific literature and demonstrate campaigns including generative design of Li-ion solid-state electrolytes, autonomous MLIP benchmarking and fine-tuning, and multi-stage virtual screening.

??? info "Relevance to DENG.Group"

Highly relevant to Yanhao Deng and the group's computational workflow. AtomisticSkills provides a pre-built agentic infrastructure for automating many tasks the group performs manually — from DFT calculations to MLIP training to high-throughput screening. The demonstrated campaign on generative design of Li-ion solid-state electrolytes directly mirrors the group's research. The framework could accelerate the group's discovery pipeline for new halide and sulfide electrolyte compositions by automating the cycle of structure generation, calculation, and analysis.

Halide Solid Electrolytes

3. [A Cost-competitive Amorphous Oxychlorophosphate Polyanion Cluster Solid Electrolyte for All-Solid-State Lithium Batteries](https://www.sciencedirect.com/science/article/abs/pii/S2211285526003630)

Source: Nano Energy (S2211285526003630) · 📅 2026-05-22 · [↗ Open paper](https://www.sciencedirect.com/science/article/abs/pii/S2211285526003630)

Reports a cost-effective polyanion-incorporated amorphous oxyhalide solid electrolyte, xLi₃PO₄-TaCl₅ (xLPTC), synthesized via low-energy ball-milling. The optimized 1/3-LPTC composition achieves 1.3 mS cm⁻¹ room-temperature ionic conductivity with 0.310 eV activation energy. The incorporation of PO₄ groups stabilizes an amorphous TaCl₆-based framework and induces local distortion of the chlorine coordination environment. DFT calculations and MLFF modeling confirm that PO₄ units distort the Cl sublattice to enable superionic conduction. Full cells (Li₀.₇In | LPSCl | 1/3-LPTC | NMC811) showed 126.7 mAh g⁻¹ initial capacity and 70% retention after 738 cycles at 1C.

??? info "Relevance to DENG.Group"

Directly relevant to the Deng group's core research on halide solid electrolytes. The polyanion-doping strategy represents a new design principle for engineering amorphous halide SSEs that the group could explore computationally using their MLIP and DFT tools. The use of MLFF (machine-learned force field) modeling to understand the conduction mechanism in the amorphous structure is exactly the type of computation Yanhao Deng performs. The cost-competitive angle (TaCl₅-based) is also notable for practical applications.

4. [NASICON-type LATP Solid Electrolytes for Lithium Metal Batteries: Fundamentals to AI-driven Materials Design](https://www.sciencedirect.com/science/article/abs/pii/S2405829726002710)

Source: Energy Storage Materials (S2405829726002710) · 📅 2026-05-20 · [↗ Open paper](https://www.sciencedirect.com/science/article/abs/pii/S2405829726002710)

A comprehensive review covering the crystal structure, Li⁺ transport mechanisms, and key limitations of LATP solid electrolytes. The review systematically covers synthesis methods, LATP/Li-metal interfacial challenges, composite and hybrid electrolyte designs, and emerging AI/ML strategies for LATP optimization. It provides a roadmap from lab studies to industrial implementation, connecting structure–processing–property relationships with bulk and grain-boundary transport alongside interface and composite strategies.

??? info "Relevance to DENG.Group"

Relevant as a reference resource for the group's broader solid electrolyte work. While LATP is an oxide SSE, the review's treatment of grain-boundary resistance, interface stability, and AI/ML-driven materials design provides transferable insights for the group's halide electrolyte research. The discussion of composite electrolyte strategies and interfacial engineering parallels challenges the group faces with halide SSE/cathode interfaces. The AI/ML section provides a useful benchmark for the group's computational approaches.

Polymer Electrolytes

5. [Artificial Crystalline-Amorphous Architecture Enables Continuous Ion Transport in Poly(Vinylidene Fluoride)-Based Solid-State Electrolytes](https://doi.org/10.1002/smll.73788)

Source: Small (10.1002/smll.73788) · 📅 2026-05-20 · [↗ Open paper](https://doi.org/10.1002/smll.73788)

Designs an 'artificial crystalline-amorphous' architecture for solid-state polymer electrolytes by infiltrating fully amorphous PVT into an oriented electrospun fibrous framework of semi-crystalline PVT. The fibrous framework serves as an 'artificial crystalline phase' providing mechanical support and facilitating lithium-salt dissociation, while the amorphous phase enables long-range ion conduction. The resulting SPEs achieve 1.23 mS cm⁻¹ at 25°C, outperforming most all-polymeric SPEs, with stable Li/Li cycling over 1300 h at 0.2 mA cm⁻² and stable NCM811/Li full-cell cycling.

??? info "Relevance to DENG.Group"

Relevant to the group's interest in solid polymer electrolytes. The artificial crystalline-amorphous architecture provides a new design principle for resolving the classic conductivity-mechanical strength trade-off in polymer electrolytes. The approach of using an electrospun fibrous framework to create continuous amorphous conduction pathways could inspire similar composite designs incorporating inorganic fillers (e.g., halide SSE particles) for the group's composite electrolyte work. The 1.23 mS cm⁻¹ conductivity is competitive with many ceramic SSEs.

ML Interatomic Potentials & Workflows

1. [TriForces: Augmenting Atomistic GNNs for Transferable Representations](https://arxiv.org/abs/2605.20581)

Source: arXiv:2605.20581 (Accepted at ICML 2026) · 📅 2026-05-20 · [↗ Open paper](https://arxiv.org/abs/2605.20581)

Presents TriForces, a model-agnostic three-stream framework that separates composition and structure information in atomistic GNNs, combined with self-supervised learning to preserve transferable representations. On the OMat24 benchmark in the limited-data regime, TriForces reduces energy MAE by 57% at 20K samples and improves force MAE across all sample sizes compared to baselines. It also enables efficient similar-structure retrieval through its learned latent space, without requiring DFT labels during pre-training.

??? info "Relevance to DENG.Group"

Directly relevant to Yanhao Deng's MLIP development work. The improved transferability of TriForces addresses a critical challenge in deploying MLIPs for battery materials, where training data is often limited. The model-agnostic design means it can be applied on top of the group's existing MACE or Allegro models for halide and oxide electrolytes, potentially improving accuracy on out-of-distribution configurations encountered at grain boundaries and interfaces.

2. [Dataset-Aware Entropy-Maximized Active Learning for Machine-Learned Interatomic Potentials](https://arxiv.org/abs/2605.20384)

Source: arXiv:2605.20384 · 📅 2026-05-19 · [↗ Open paper](https://arxiv.org/abs/2605.20384)

Proposes an active learning framework that combines local entropy-driven molecular dynamics with global dataset-aware filtering to efficiently select training structures for MLIPs. The method uses a log-determinant of fingerprint covariance to select only configurations providing genuinely new information, employing dual covariance modes for ordered and disordered phases. Demonstrated on carbon, silicon, and NaCl systems, entropy-driven sampling achieves 3–10× lower energy MAE compared to random MD sampling at matched training set sizes of 100–800 structures.

??? info "Relevance to DENG.Group"

Highly relevant to Yanhao Deng's MLIP training pipeline. The dramatic improvement in data efficiency means the group could achieve high-quality potentials for complex solid electrolyte systems (halides, sulfides) with far fewer expensive DFT calculations. The dual covariance modes for ordered and disordered phases are particularly valuable for modeling doped halide electrolytes where partial occupancies and configurational disorder are common.

3. [Lang2MLIP: End-to-End Language-to-Machine Learning Interatomic Potential Development with Autonomous Agentic Workflows](https://arxiv.org/abs/2605.14527)

Source: arXiv:2605.14527 · 📅 2026-05-14 · [↗ Open paper](https://arxiv.org/abs/2605.14527)

Introduces Lang2MLIP, a multi-agent framework that takes natural-language input and formulates end-to-end MLIP development as a sequential decision-making problem solved by large language models. At each step, a decision-making agent observes the current dataset, model, and evaluation results, then automatically selects an appropriate action to improve the model—removing the need for a predefined pipeline. The framework is evaluated on a solid electrolyte interphase (SEI) system with multiple components and interfaces.

??? info "Relevance to DENG.Group"

Directly relevant to Yanhao Deng's computational workflow. Lang2MLIP's application to SEI systems with multiple components and interfaces closely mirrors the Deng group's challenge of building MLIPs for complex electrode–electrolyte interfaces. The agentic self-correction capability, where the system revisits earlier stages when failures arise, could automate the iterative training loop that is currently a major bottleneck in the group's MLIP development for halide and sulfide electrolyte systems.

4. [Upscaling DFT-Trained Machine-Learning Interatomic Potential toward Quantum Monte Carlo Accuracy: Sulfur-Vacancy Migration in Monolayer MoS₂ as a Testbed](https://arxiv.org/abs/2605.22601)

Source: arXiv:2605.22601 · 📅 2026-05-21 · [↗ Open paper](https://arxiv.org/abs/2605.22601)

Demonstrates a multi-fidelity approach to train MLIPs at quantum Monte Carlo (QMC) accuracy by fine-tuning only the readout layers of a DFT-trained MACE model using a limited dataset of QMC energies alongside DFT forces. Applied to sulfur vacancy migration in monolayer MoS₂, the QMC-fine-tuned potential significantly improves both energetics and atomic forces over the DFT baseline. The method opens the door to large-scale near-QMC-quality simulations that would be impossible with brute-force QMC.

??? info "Relevance to DENG.Group"

Relevant to Yanhao Deng's MLIP accuracy goals. The multi-fidelity approach of fine-tuning only readout layers with limited high-level data is a practical strategy the group could adopt to improve the accuracy of their battery material MLIPs beyond DFT level, particularly for critical configurations like transition states for Li⁺ migration. The methodology could be applied to upgrade existing DFT-trained potentials for halide electrolytes using higher-level calculations on a small, targeted subset of configurations.

Solid Electrolytes & Ionic Conductors

5. [Ordered–Disordered Ionic Cocrystalline Solid-State Electrolytes for Rapid Ion Migration in Sodium Metal Batteries](https://pubs.acs.org/doi/10.1021/jacs.6c01095)

Source: Journal of the American Chemical Society (10.1021/jacs.6c01095) · 📅 2026-05-22 · [↗ Open paper](https://pubs.acs.org/doi/10.1021/jacs.6c01095)

Reports an ionic cocrystalline solid-state electrolyte, NaClO₄(SN)₃, featuring a unique ordered–disordered hybrid lattice with an ordered Na⁺-coordination backbone and orientationally disordered succinonitrile molecules serving as ionic pathways. The electrolyte achieves 0.94 mS cm⁻¹ ionic conductivity at 25 °C with a low activation energy of 0.26 eV, an electrochemical stability window beyond 4.6 V vs Na/Na⁺, and a melting point of 36.2 °C enabling in situ melting infiltration into electrodes for conformal interfaces.

??? info "Relevance to DENG.Group"

Highly relevant to the Deng group's expanding work on sodium solid-state batteries. The ordered–disordered cocrystal engineering strategy provides a new design principle that Mengke Li and Yan Li could explore computationally. The in situ melting infiltration approach addresses the interfacial contact challenge that is critical for solid-state battery performance. The group's computational tools could be used to screen for alternative cocrystal compositions with similar or improved Na⁺ conductivity.

6. [Phosphonium Poly(Ionic Liquid) Electrolytes for Fast Lithium-Ion Conduction](https://pubs.acs.org/doi/10.1021/jacs.6c02428)

Source: Journal of the American Chemical Society (10.1021/jacs.6c02428) · 📅 2026-05-22 · [↗ Open paper](https://pubs.acs.org/doi/10.1021/jacs.6c02428)

Introduces a new class of solid polymer electrolytes based on phosphonium poly(ionic liquid)s that outperform their ammonium counterparts. The poly(DADMP)FSI:LiFSI 1:1.5 composition achieves 1.5 × 10⁻³ S cm⁻¹ at 80 °C and 1.5 × 10⁻⁴ S cm⁻¹ at 30 °C, with a high lithium transference number of 0.6–0.7 and electrochemical stability beyond 4.5 V. MD simulations reveal that the larger, more flexible phosphonium cation enables weaker cation–anion interactions and faster ion transport compared to ammonium analogues.

??? info "Relevance to DENG.Group"

Relevant to the group's interest in solid polymer electrolytes. The phosphonium poly(IL) design principle could inspire computational screening of alternative cation chemistries for polymer electrolytes. The MD simulation methodology used to understand ion coordination environments and transport mechanisms parallels the group's computational approach. The finding that single-anion (FSI) systems outperform mixed-anion (FSI/TFSI) systems in phosphonium backbones provides a useful reference for the group's work on anion effects in electrolyte design.

Defects & Interfaces

7. [AI-Screened Small-Molecule Templating Effect Enabling 2D Architectures for Dendrite-Free Lithium Metal Batteries](https://www.cell.com/matter/abstract/S2590-2385(26)00079-2)

Source: Matter (10.1016/j.matt.2026.00079) · 📅 2026-05-22 · [↗ Open paper](https://www.cell.com/matter/abstract/S2590-2385(26)00079-2)

Develops an AI-assisted screening workflow that identified sucrose and citric acid as a synergistic molecular couple guiding 2D crystallization of Li₆.₂₅Al₀.₂₅La₃Zr₂O₁₂ (LALZO) nanosheets for composite polymer electrolytes. The resulting brick-and-mortar-like architecture establishes continuous Li⁺ transport highways while providing robust physical barriers against dendrite growth. The LNSs@PEO composite enables stable cycling over 3,000 h in lithium metal cells, with full cells retaining 96.7% capacity after 300 cycles.

??? info "Relevance to DENG.Group"

Directly relevant to Cheng Peng's interface and dendrite studies. The AI-driven molecular screening approach for designing 2D ceramic fillers could be adapted for computational screening of templating molecules for halide electrolyte synthesis. The brick-and-mortar architecture provides a concrete mechanical model that could be simulated using the group's computational tools to understand how 2D fillers deflect dendrite growth. The 3,000-hour cycling stability demonstrates the practical impact of combining continuous Li⁺ pathways with mechanical reinforcement.

8. [Saddle-Node Bifurcation in Interfacial Morphology Selects Battery Degradation Phase](https://arxiv.org/abs/2605.10252)

Source: arXiv:2605.10252 · 📅 2026-05-11 · [↗ Open paper](https://arxiv.org/abs/2605.10252)

Proposes a minimal nonlinear closure ODE for the dynamic active-area factor of a battery interface that exhibits a saddle-node bifurcation separating a smooth passivating phase from a morphologically unstable phase. Maps four canonical anode configurations (graphite, silicon composite, lithium metal, and anode-free Li/Cu) onto the closure using long-cycle experimental data, finding that the anode-free configuration sits within 5% of the critical threshold. Derives three falsifiable predictions (critical current density, critical temperature shift, and critical-slowing-down exponent) consistent with available data.

??? info "Relevance to DENG.Group"

Relevant to the group's phase-field and dendrite growth modeling work. The saddle-node bifurcation framework provides a new analytical tool for understanding the sharp transition between stable and unstable deposition in solid-state batteries. The finding that anode-free configurations sit near the critical threshold has direct implications for the group's work on lithium metal and anode-free solid-state battery designs. The analytical predictions could be validated against the group's phase-field simulations of dendrite growth in solid electrolytes.

ML Interatomic Potentials & Uncertainty Quantification

1. [Uncertainty-aware Machine Learning Interatomic Potentials via Learned Functional Perturbations](https://arxiv.org/abs/2605.19939)

Source: arXiv:2605.19939 · 📅 2026-05-19 · [↗ Open paper](https://arxiv.org/abs/2605.19939)

Proposes a simple method to turn any deterministic MLIP into a probabilistic one through learned functional perturbations, finetuned end-to-end with the Continuous Ranked Probability Score (CRPS). The approach avoids the architectural complexity of variational inference or ensemble methods. On the N-body charged particle benchmark, the P-EGNN model improves CRPS over the state-of-the-art Bayesian MLIP (BLIP) by 19–32%, and on silica, P-Orb raises Spearman correlation between predicted uncertainty and actual error from 0.75 to 0.84.

??? info "Relevance to DENG.Group"

Directly relevant to Yanhao Deng's MLIP development work. Robust uncertainty quantification is essential for safe deployment of MLIPs in battery materials simulations, where silent failures on out-of-distribution configurations can lead to erroneous predictions of Li⁺ migration barriers or interfacial stability. The simplicity of the approach — no ensembles or variational inference needed — makes it practical to integrate into the group's existing MLIP training workflows for halide and oxide electrolytes.

2. [Atomistic Modeling of Chemical Disorder in Materials: Bridging Classical Methods and AI-Assisted Approaches](https://arxiv.org/abs/2605.19124)

Source: arXiv:2605.19124 · 📅 2026-05-18 · [↗ Open paper](https://arxiv.org/abs/2605.19124)

A comprehensive review examining how classical and AI-driven methods can bridge the representation gap between experimentally reported disorder (partial occupancies, ensemble averages) and atomistic simulations (fully specified configurations). The review covers mean-field theories, cluster expansion, quasi-random approximations, Monte Carlo, and emerging AI approaches including universal interatomic potentials and generative models for disordered structures. It outlines a roadmap toward disorder-native AI that transforms chemical disorder from a representational obstacle into a controllable variable.

??? info "Relevance to DENG.Group"

Highly relevant to the Deng group's computational materials research. Many solid electrolytes of interest — including halide systems with mixed cation/anion occupancy, doped Li₃YCl₆ variants, and anti-perovskites — exhibit chemical disorder that is difficult to model with idealized structures. The review's framework for converting averaged disorder descriptions into representative configurational ensembles could improve the accuracy of the group's DFT and MLIP calculations for doped halide electrolytes and grain boundary structures studied by Cheng Peng.

Solid Electrolytes & Interfaces

3. [Sodium Halide Solid Electrolytes for All-Solid-State Sodium Batteries](https://www.sciencedirect.com/science/article/abs/pii/S2405829726001753)

Source: Energy Storage Materials (10.1016/j.ensm.2026.03.175) · 📅 2026-05-20 · [↗ Open paper](https://www.sciencedirect.com/science/article/abs/pii/S2405829726001753)

Reports on sodium halide solid electrolytes developed specifically for all-solid-state sodium batteries. The work addresses the challenge of achieving high Na⁺ conductivity in halide frameworks while maintaining electrochemical stability against both Na metal anodes and high-voltage cathodes, extending the successful lithium halide design principles to the sodium system.

??? info "Relevance to DENG.Group"

Directly relevant to the group's interest in both halide solid electrolytes and sodium-ion systems. The extension of halide electrolyte chemistry from Li to Na opens a new computational design space for the group. Mengke Li and Yan Li could apply the group's high-throughput screening and DFT methods to explore Na halide phase stability and ionic conductivity, complementing their existing work on Li halide systems.

4. [Mechanochemical-Induced Halide Segregation for Highly Stable All-Solid-State Lithium Batteries](https://www.sciencedirect.com/science/article/abs/pii/S2405829726001819)

Source: Energy Storage Materials (10.1016/j.ensm.2026.03.181) · 📅 2026-05-15 · [↗ Open paper](https://www.sciencedirect.com/science/article/abs/pii/S2405829726001819)

Reports a mechanochemical-induced halide segregation strategy that forms a stable interphase at the electrode-electrolyte interface in all-solid-state lithium batteries. The segregated interphase provides a holistic solution to interfacial challenges including chemical instability and poor contact, demonstrating significantly improved cycling stability in full cells.

??? info "Relevance to DENG.Group"

Directly relevant to the Deng group's halide electrolyte research and interface stability studies. The mechanochemical approach to engineering interfacial halide segregation provides a new design principle that could be explored computationally to understand the thermodynamic driving forces for segregation and the resulting interphase properties. Cheng Peng could apply computational tools to model the segregated interphase structure and its impact on Li⁺ transport at grain boundaries and interfaces.

5. [From Powder to Product: A Perspective on Halide Electrolytes for Commercial Lithium Solid-State Batteries](https://link.springer.com/article/10.1007/s42864-026-00378-9)

Source: Tungsten (10.1007/s42864-026-00378-9) · 📅 2026-04-22 · [↗ Open paper](https://link.springer.com/article/10.1007/s42864-026-00378-9)

A comprehensive perspective examining structure–property relationships across trigonal, spinel, and emerging oxyhalide frameworks for halide solid electrolytes. The paper emphasizes how aliovalent doping, mixed-anion strategies, and Earth-abundant chemistries expand the halide design space. It evaluates scalable synthesis pathways — from mechanochemical milling to melt processing — and provides a roadmap for halide-based solid-state battery development, including a comparative analysis with sulfide and oxide systems.

??? info "Relevance to DENG.Group"

A valuable reference for the entire Deng group's halide electrolyte research. The systematic comparison of trigonal, spinel, and oxyhalide frameworks and their structure-property relationships provides clear targets for computational screening. The roadmap from synthesis to commercialization helps frame the group's computational work within the broader context of practical battery development. The discussion of Earth-abundant chemistries could guide the group toward more commercially relevant halide compositions.

Polymer Electrolytes & Interface Engineering

6. [Intramolecular Design of Poly(ethylene oxide) for Solid-State Electrolytes and Next-Generation High-Energy Batteries](https://link.springer.com/article/10.1007/s40820-026-02161-4)

Source: Nano-Micro Letters (10.1007/s40820-026-02161-4) · 📅 2026-05-18 · [↗ Open paper](https://link.springer.com/article/10.1007/s40820-026-02161-4)

Reviews intramolecular design strategies for PEO-based solid-state electrolytes, covering molecular chain architecture modifications, segmental motion engineering, and coordination environment tuning to overcome PEO's low room-temperature ionic conductivity (~10⁻⁷ S cm⁻¹). The work connects molecular-level design to macroscopic performance metrics relevant to achieving >500 Wh kg⁻¹ energy density with lithium metal anodes in solid-state configurations.

??? info "Relevance to DENG.Group"

Relevant to the group's interest in solid polymer electrolytes and polymer-ceramic composite systems. The intramolecular design principles — particularly the relationship between chain architecture, segmental dynamics, and ion transport — provide molecular-level targets that could be explored computationally. The review's framework for connecting molecular design to cell-level performance aligns with the group's multiscale modeling approach.

7. [Electrolyte Design and Interface Engineering for High-Voltage Solid-State Lithium Batteries](https://www.frontiersin.org/journals/chemistry/articles/10.3389/fchem.2026.1840199/full)

Source: Frontiers in Chemistry (10.3389/fchem.2026.1840199) · 📅 2026-05-12 · [↗ Open paper](https://www.frontiersin.org/journals/chemistry/articles/10.3389/fchem.2026.1840199/full)

A systematic review covering electrolyte design strategies for high-voltage solid-state lithium batteries (above 4.3 V vs. Li⁺/Li). The review covers inorganic solid electrolytes, polymer electrolytes, organic–inorganic composites, gel polymer electrolytes, and quasi-solid-state electrolytes, with emphasis on cathode-side stabilization strategies, interphase regulation, and coating design. The work highlights the synergistic optimization needed between electrolyte chemistry, interfacial stability, and scalable processing.

??? info "Relevance to DENG.Group"

Relevant to the entire Deng group. The high-voltage stability challenge is critical for halide electrolyte applications with high-energy cathodes like NCM. The review's discussion of interphase regulation and coating strategies provides experimental context for the group's computational studies of interface stability and thermodynamic compatibility between halide electrolytes and cathode materials.

Sodium Batteries & Cross-Cutting Reviews

8. [Navigating Interfaces in Solid-State Sodium Batteries: Challenges, Solutions, and Future Directions](https://pubs.rsc.org/en/content/articlehtml/2026/ee/d6ee01558a)

Source: Energy & Environmental Science (10.1039/D6EE01558A) · 📅 2026-05-19 · [↗ Open paper](https://pubs.rsc.org/en/content/articlehtml/2026/ee/d6ee01558a)

A comprehensive review examining interfacial challenges in solid-state sodium batteries including dendrite growth, unstable interphases, mechanical degradation, electrochemical instability, and phase transitions. The review covers advanced material design (solid-state electrolytes, composite electrodes, interlayers), computational approaches (first-principles, molecular dynamics, multi-scale modeling), and interface characterization techniques. It emphasizes the role of AI and machine learning in accelerating solutions for SSSB interface optimization.

??? info "Relevance to DENG.Group"

Highly relevant to the group's expanding work on sodium solid-state batteries. The systematic catalog of interfacial failure modes and computational approaches directly parallels the group's existing work on lithium solid-state battery interfaces. The discussion of first-principles and MD methods for interface optimization could guide the group's computational strategy as they extend their halide electrolyte expertise to sodium systems.

ML Interatomic Potentials & Free Energy

1. [Reweighting Free Energy Profiles Between Universal Machine Learning Interatomic Potentials for Fast Consensus Building](https://arxiv.org/abs/2605.15630)

Source: arXiv:2605.15630 · 📅 2026-05-15 · [↗ Open paper](https://arxiv.org/abs/2605.15630)

Presents a systematic framework for reweighting potential-of-mean-force (PMF) profiles, initially sampled with a single source MLIP, across multiple target MLIPs. Uses robust analytical corrections (mean energy-gap approximation) to bypass statistical collapse when phase-space overlap between potentials is critically low. Demonstrated on a 601-atom Li⁺ transport system in a nanoconfined electrolyte, recovering high-fidelity thermodynamics across PBE+D3, PBE-sol, r²SCAN, and r²SCAN-D4 reference levels at a fraction of the cost of full simulations.

??? info "Relevance to DENG.Group"

Highly relevant to Yanhao Deng's MLIP development. The reweighting framework enables affordable cross-model consensus on ion-transport free energy barriers without redundant DFT simulations. The Li⁺ nanoconfined-transport application directly parallels the group's work on Li⁺ migration in grain boundaries and interfaces of solid electrolytes. The finding that MLIPs partition into distinct clusters based on training data has implications for how the group selects and validates potentials for battery materials.

2. [An Agentic Workflow for Autonomous Transition State Search](https://arxiv.org/abs/2605.14154)

Source: arXiv:2605.14154 · 📅 2026-05-13 · [↗ Open paper](https://arxiv.org/abs/2605.14154)

Proposes TSAgent, an agentic workflow that automates transition-state search at DFT-level accuracy through a persistent plan-execute-analyze-replan loop. Evaluated on 100 examples from the OC20NEB heterogeneous catalysis benchmark, TSAgent achieves 83% success rate. In direct comparison against expert DFT practitioners on 10 held-out examples, TSAgent achieves 70% success versus human-expert average of 73±12%. Independently reproduces Brønsted-Evans-Polanyi scaling relationships for NH₃ dissociation on metal and single-atom alloy surfaces.

??? info "Relevance to DENG.Group"

Directly relevant to Yanhao Deng's computational workflow. Transition-state searches are critical for calculating Li⁺ migration barriers, interfacial reaction pathways, and degradation mechanisms in solid-state batteries. TSAgent could automate the tedious NEB/CI-NEB workflow that is currently a major bottleneck for studying electrode-electrolyte interface reactions. The agentic plan-replan loop approach complements the group's existing DFT calculations for halide and sulfide electrolyte stability.

Solid Electrolytes & Interfaces

3. [Bulk-to-Interface Fluorination for Stable and Low-Pressure All-Solid-State Lithium Metal Batteries](https://www.nature.com/articles/s41467-026-73012-4)

Source: Nature Communications (10.1038/s41467-026-73012-4) · 📅 2026-05-14 · [↗ Open paper](https://www.nature.com/articles/s41467-026-73012-4)

Designs a core-shell structured sulfide electrolyte (Li₅.₄PS₄.₄Cl₁.₄F₀.₂-0.2LiF) with a 50 nm LiF nanoshell and F-enriched bulk via fast thermodynamic diffusion of fluorine atoms. During cycling, F atoms diffuse into the NCM cathode lattice, enhancing structural robustness and mitigating mechanochemical failure, while the LiF nanoshell stabilizes both Li metal and cathode interfaces. Pouch cells achieve stable cycling over 350 cycles at 1 C under only 2.5 MPa stack pressure, with >400 Wh/kg specific energy.

??? info "Relevance to DENG.Group"

Highly relevant to the entire Deng group's solid-state battery research. The bulk-to-interface fluorination strategy provides a new design principle for achieving low-pressure operation, which is critical for practical ASSBs. The LiF nanoshell concept could be explored computationally to understand interfacial thermodynamics and F-diffusion kinetics. Cheng Peng could apply the group's computational tools to model F diffusion at grain boundaries and interfaces in halide electrolytes.

4. [Amorphous Sulfo-Halide Solid Electrolytes With Enhanced Anion Dynamics for Highly Stable All-Solid-State Sodium Batteries](https://advanced.onlinelibrary.wiley.com/doi/10.1002/aenm.71091)

Source: Advanced Energy Materials (10.1002/aenm.71091) · 📅 2026-05-18 · [↗ Open paper](https://advanced.onlinelibrary.wiley.com/doi/10.1002/aenm.71091)

Develops amorphous sulfo-halide solid electrolytes with enhanced anion dynamics for all-solid-state sodium batteries. The amorphous structure provides superior deformability, stable high-voltage cycling, and excellent interfacial contact under moderate stack pressures. The mixed-anion design strategy leverages the coexistence of sulfide and halide anions to achieve high Na⁺ conductivity while maintaining electrochemical stability against both Na metal and high-voltage cathodes.

??? info "Relevance to DENG.Group"

Directly relevant to the group's interest in halide solid electrolytes and sodium-ion systems. The sulfo-halide mixed-anion approach extends the design space beyond pure chloride or bromide halides. The amorphous structure strategy addresses the grain-boundary resistance problem that Cheng Peng studies. The sodium-ion focus opens computational opportunities for the group to explore Na⁺ migration in amorphous vs. crystalline sulfo-halide environments using MLIP-driven MD simulations.

Cross-Scale Modeling & Reviews

5. [AI-Enabled Cross-Scale Modeling and Parameter Transfer for Lithium-Ion Batteries](https://www.sciencedirect.com/science/article/abs/pii/S2405829726003557)

Source: Energy Storage Materials (10.1016/j.ensm.2026.scaff) · 📅 2026-05-15 · [↗ Open paper](https://www.sciencedirect.com/science/article/abs/pii/S2405829726003557)

Proposes the AI-enabled Cross-Scale Parameter Chain (ACPC) as a carrier-centered framework for cross-scale LIB modeling. The framework traces how physically meaningful quantities are generated at atomic scales, transformed across model interfaces, compressed into deployable descriptors, and updated through operational feedback. Reviews AI's role at each interface: parameter inversion, structure reconstruction, surrogate acceleration, uncertainty-aware compression, and online recalibration across atom-to-module scales.

??? info "Relevance to DENG.Group"

A valuable reference for the Deng group's computational strategy. The ACPC framework formalizes how atomistic calculations (DFT, MLIP-MD) feed into electrode- and cell-level models, which is exactly the challenge the group faces in connecting MLIP predictions to battery-level performance. The discussion of uncertainty-aware compression and parameter transfer is particularly relevant for Yanhao Deng's MLIP development, ensuring that atomistic accuracy propagates meaningfully to engineering-scale predictions.