High-Throughput Discovery of Li3Sc2(PO4)3 as a Protective Coating for Stabilizing Mid-Ni NCM Interfaces in All-Solid-State Batteries

High-Throughput Discovery of Li3Sc2(PO4)3 as a Protective Coating for Stabilizing Mid-Ni NCM Interfaces in All-Solid-State Batteries | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article High-Throughput Discovery of Li 3 Sc 2 (PO 4 ) 3 as a Protective Coating for Stabilizing Mid-Ni NCM Interfaces in All-Solid-State Batteries Ji Hoon Kim, Seunghyun Lee, Sang Uck Lee This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9450434/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract As all-solid-state battery (ASSB) technologies continue to advance, interest has resurfaced in mid-nickel (mid-Ni) LiNiCoMnO (NCM; x = 0.5) cathodes due to their enhanced structural stability, reduced oxygen evolution, and higher capacities at elevated cutoff voltages compared to high-nickel compositions. However, interfacial degradation including parasitic reactions with solid-state electrolytes (SSEs) remains a major challenge. To address this issue, we conducted a high-throughput computational screening of oxide-based coating materials, evaluating their electrochemical stability, interfacial robustness, and Li-ion conductivity using Li–Li network descriptors. From this screening, 8 candidates were selected based on strict criteria. Among them, LiSc(PO) emerged as a particularly promising coating material, exhibiting strong electrochemical stability under high-voltage conditions (> 4 V) and substantial ionic conductivity (0.2 mS/cm), exceeding that of most oxide-type SSEs, as confirmed by ab initio molecular dynamics (AIMD) simulations. Furthermore, large-scale molecular dynamics simulations using a universal machine-learning interatomic potential (uMLIP) demonstrate its ability to suppress surface degradation of mid-Ni NCM and prevent [PS] decomposition in LiPSCl, confirming its potential as a protective coating. These findings highlight the effectiveness of our computational screening strategy for coating-material discovery and underscore the potential of LiSc(PO) as a robust interfacial layer for stabilizing mid-Ni ASSBs. Mid-nickel cathode High-throughput screening (HTS) Coating materials Density functional theory (DFT) and Machine learning interatomic potential (MLIP) Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction The global transition toward carbon neutrality, combined with the rapid commercialization of electric vehicles (EVs), has significantly accelerated the demand for safer and cleaner energy storage technologies. Among the various options, lithium-ion batteries (LIBs) have emerged as the most promising technology due to their high energy density, long cycle life, and well-established manufacturing infrastructure [ 1 , 2 ]. However, to meet the rigorous requirements of next-generation EVs, such as driving range of over 300 miles per charge, LIBs must continue to improve both performance and safety. Conventional LIBs typically used flammable organic liquid electrolytes, which introduce inherent safety risks, particularly under thermal runaway conditions [ 3 , 4 ]. The development of all-solid-state batteries (ASSBs) have gained widespread attention as a promising alternative by introducing inorganic solid-state electrolytes (SSEs), enabling improved safety and increase capacity without separator [ 5 – 8 ]. Furthermore, SSEs allow for the use of lithium metal anodes, offering the potential to significantly increase energy density. Beyond the benefits offered by SSEs, another common strategy to enhance the energy density of ASSBs is increasing the nickel content of cathode materials. Among the various components of ASSBs, the cathode plays a critical role in determining overall energy density and cycling performance. In particular, high-nickel (high-Ni) (Ni ≥ 80%) layered structures, such as LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NCM811), have been widely investigated due to their high specific capacity and reduced cobalt content [ 9 ]. Despite these notable advantages of high-Ni systems, these materials suffer from intrinsic limitations associated with their high-Ni content. As the nickel concentration increases, the cathode surface becomes significantly reactive, leading to irreversible phase transformation into a rock-salt structure and the release of lattice oxygen during delithiation [ 10 – 14 ]. These degradation processes trigger structural instability, metal dissolution, and parasitic reactions, ultimately deteriorating battery performance and safety. Moreover, high-Ni cathodes are susceptible to the formation of residual lithium compounds and demonstrate poor interfacial compatibility with SSEs, further accelerating degradation over prolonged cycling [ 11 ]. In response to these issues and growing demands for cost reduction, mid-nickel (mid-Ni) layered oxide cathodes, containing approximately 50–60% nickel such as LiNi 0.6 Co 0.2 Mn 0.2 O 2 (NCM622) and LiNi 0.5 Co 0.2 Mn 0.3 O 2 (NCM523), have attracted renewed attention as more balanced alternative to high-Ni systems due to their optimal trade-off between energy density and structural stability [ 15 – 17 ]. The reduced nickel content mitigates surface reactivity, resulting in improved cycling stability and simultaneously contributes to a cost reduction. Although mid-Ni cathodes offer lower theoretical capacity compared to high-Ni counterparts, operating them at higher voltages (≥ 4.2 V) can compensate for the capacity loss, enabling them to meet the energy requirements of high-performance batteries [ 15 , 18 – 20 ]. Nevertheless, achieving stable high-voltage operation of mid-Ni cathodes in ASSBs remain challenges. At elevated voltages, mid-Ni are still vulnerable to surface degradation and interfacial side reactions with SSEs during extended cycling [ 14 , 21 ]. To this end, surface coating strategies have been extensively explored for numerous battery systems. Applying a protective coating layer to the cathode particles can physically separate the active material from the SSE, minimize undesired chemical reactions, and promote the formation of a robust and ionically conductive cathode–electrolytes interphase. These coatings effectively reduce transition metal dissolution, oxygen loss, and structural decomposition under high-voltage operation, thereby improving long-term cycling performance [ 16 , 17 , 22 , 23 ]. A wide range of coating materials including metals, semi-metals, and non-metals has been actively investigated, and many of them have demonstrated a significant ability to stabilize interface between the cathode and electrolyte [ 24 – 29 ]. However, most reported coating materials to date are based on previously researched systems, and there remains a critical need to discover novel coating candidates specifically tailored for mid-Ni cathodes and stable operation under high-voltage conditions. In this context, computational high-throughput screening (HTS) approaches offer an efficient pathway to identify promising candidates across large material databases without relying on time-consuming experimental trial-and error. Such methods including density functional theory (DFT) enable rapid evaluation of electrochemical, interfacial compatibility, and ionic transport performance, resulting in accelerating the discovery of novel materials. These computational strategies have already been successfully applied not only to coating materials, but also across various functional domains, including oxide-based SSEs [ 30 – 32 ]. Here, we conducted a data-driven computational HTS approach of oxide-based coating materials to identify novel candidates suitable for high-voltage mid-Ni cathodes. From materials project (MP) database [ 33 ], lithium- and oxygen- containing materials were evaluated using computational descriptors including electrochemical window (ECW), interfacial stability, band gap, and Li–Li networks, leading to the identification of 88 screened candidates. Based on these candidates, 8 structures were further selected using strict criteria of high-voltage stability (> 4 V) and interfacial stability. Among these candidates, Li 3 Sc 2 (PO 4 ) 3 exhibited outstanding properties, including electrochemical stability above 4 V, excellent interfacial compatibility with both the mid-Ni cathode and the Li 6 PS 5 Cl (LPSC) SSE, a wide band gap, and high Li-ion diffusivity. To consider its experimentally observed structural forms, prior studies show that this composition exists in three experimental phases (α, β, and γ-phases). Notably, our ab initio molecular dynamics (AIMD) calculations demonstrate that the γ-phase (the structure identified in our screening) exhibits superior ionic conductivity (~ 0.2 mS/cm), exceeding that of most oxide-type SSEs [ 34 – 36 ]. This superior ionic conductivity was further supported by probability density analysis, which revealed a well-defined Li-ion diffusion pathway. To further evaluate interfacial stability, 500 ps molecular dynamics (MD) simulations of the cathode/LPSC interface were carried out using a universal machine-learning interatomic potential (uMLIP). The results demonstrate that direct contact between NCM523 and LPSC leads to PS 4 decomposition in LPSC and nickel dissolution into the electrolyte, which destabilizes the interfacial structure. In contrast, introducing Li 3 Sc 2 (PO 4 ) 3 as a coating layer results in minimal reaction products, a stable interface, and suppressed PS 4 decomposition within the bulk region. Based on these superior properties, Li 3 Sc 2 (PO 4 ) 3 is expected to serve as an effective coating material for mid-Ni cathodes. These results highlight the importance of systematic computational materials design in next-generation ASSBs, particularly by enabling the discovery of effective coating materials that stabilize the interface between SSEs and mid-Ni cathodes. 2. Computational details All DFT calculations and MD simulations were performed with the Vienna ab initio simulation package (VASP 5.4.4) [ 37 – 40 ] and a large-scale atomic/molecular massively parallel simulator (LAMMPS) [ 41 ] package, respectively. Structural optimization was conducted using the projector augmented wave (PAW) [ 42 , 43 ] method and the Perdew-Burke-Ernzerohf (PBE) generalized gradient approximation (GGA) [ 44 ] functional. Lattice constants and internal atomic positions were fully relaxed until the residual forces reached < 0.04 eV/Å. Spin-polarized calculations were performed for systems containing 3d transition metals. The AIMD simulations were performed with an NVT Nose-Hoover thermostat [ 45 , 46 ] for the fully relaxed geometry to obtain Li-ion diffusivity during 20 ps at 1000 K. The simulation parameters (cell size, spin, and simulation temperatures) were adopted from our previous work [ 47 – 49 ]. Additional AIMD simulation were carried out from 900 K to 1200 K in 100 K intervals to estimate Li-ion conductivity at room temperature using an Arrhenius extrapolation. A gamma-centered 1 × 1 × 1 k -point mesh and a time step of 2 fs were used. Details of the procedure to obtain \(\:{\sigma\:}_{RT}\) are described in supplementary information. All structures, reference formation energies, and bandgap were obtained from the MP database [ 33 ]. ECW was evaluated using the grand potential phase diagram approach, in which the stability of each compound was assessed as a function of lithium chemical potential [ 50 , 51 ]. Phase stability was determined by constructing convex hulls in the relevant chemical spaces and calculating the energy above hull for each compound based on the same database [ 52 ]. Further details of these calculations are provided in supplementary information. Among the various types of machine-learning interatomic potentials (MLIPs), the Scalable EquiVariance-Enabled Neural Network (SevenNet) was selected to perform MD simulations using the 7 net-0 pretrained model with LAMMPS [ 53 ]. 3. Results and discussion 3.1. High-throughput screening of cathode coating oxide materials Ideal coating materials for ASSBs must meet multiple stringent criteria, such as electrochemical stability, efficient ionic transport, and interfacial compatibility with both electrodes and SSEs. These requirements become particularly important for mid-Ni cathodes due to their relatively high operating voltages, which are essential to maintain equivalent energy density compared to high-Ni cathode. Consequently, the pool of viable coating materials is severely limited, making it difficult to identify candidates that simultaneously fulfill all critical properties. To overcome this, we adopted a HTS approach aimed at theoretically discovering promising coating materials for stabilizing the interface between mid-Ni cathodes and SSEs in ASSBs. HTS enables the rapid and consistent discovery of new materials by using clearly defined property criteria, offering a systematic and reproducible way that is especially effective in theoretical computational research due to its uniform evaluation standards. Figure 1 shows the overall HTS workflow used in this study. To discover novel coating materials, we systematically conducted a top-down screening process to evaluate electrochemical, interfacial, electronic stabilities, and ionic transport properties across an extensive dataset. This approach enabled the identification of several candidates that satisfied all targeted criteria, and Li 3 Sc 2 (PO 4 ) 3 emerged as the most favorable material in the final screening stage. Initially, the early-stage dataset was constructed by retrieving 17,230 Li- and O- containing oxide crystal structures from the MP database. Oxide-based materials were selected due to their intrinsic high electrochemical stability and established use in various coating applications. For a more detailed understanding of compositional trends, we categorized the retained compounds according to the type of composed elements excluding Li and O (metals, metalloids(semi-metals), non-metals, and radioactive elements), as summarized in Fig. S1 . To refine these datasets, we excluded structures containing radioactive elements or featuring more than two additional elements beyond Li and O. Among candidates with identical compositions, only the structure with the lowest formation energy was selected to represent that composition, ensuring focus on thermodynamically stable phases. Through this filtering process, we finalized a screening pool of 4,634 structures. These preprocessing steps were critical not only for enhancing the efficiency of the HTS process but also for prioritizing materials with greater experimental feasibility. Considering the harsh battery operating conditions, coating materials should possess intrinsic electrochemical stability, characterized by a wide ECW that ensures resistance to decomposition under both oxidative and reductive environments. In this regard, we calculated the theoretical ECW for each candidate materials. By applying cutoff criteria of oxidation voltage above 3.5 V and reduction voltage below 2 V, a total of 265 materials were identified as electrochemically stable. Figure 2 a clearly demonstrates that although many materials satisfy either the oxidative or reductive stability conditions, only a limited subset fulfills both simultaneously. This subset encompasses not only widely adopted coating materials such as Li 3 PO 4 , LiNbO 3 , and LiAlO 2 but also high-voltage candidates like LiRb 2 AsO 4 , which withstands potentials up to 6.5 V as shown in Fig. 2 b [ 54 – 56 ]. Moreover, Li 2 SO 4 , a known product of solid electrolyte interphase (SEI) formation, was also included among the screened candidates. Its presence supports the interpretation that the SEI layer forms spontaneously due to its inherent electrochemical stability [ 57 ]. These findings indicate that our ECW-based filtering approach is both theoretical and experimental reasonable observation, demonstrating its reliability for discovering stable coating materials. While electrochemical stability is a critical prerequisite, coating materials must also demonstrate robust interfacial stability with both the cathode and SSEs. An ideal coating material must prevent direct chemical reactions between the cathode and electrolyte, while simultaneously allowing efficient Li-ion transport across the interface. To evaluate this requirement, we assessed the interfacial reaction energies (∆E rxn ) between each screened candidate and both the cathode and the SSE. NCM523 and LPSC were selected as representative materials of a layered mid-Ni cathode and SSE with high ionic conductivity, respectively [ 58 ]. Adopting the criterion established in previous research, we regarded candidates with ∆E rxn ≥ − 100 meV/atom as interracially compatible with both NCM523 and LPSC [ 30 ]. As shown in Fig. 2 c, a total of 154 materials satisfy this threshold, representing approximately a 50% reduction from the previous screening step and highlighting the stringency of the applied criterion. Notably, while many materials exhibited stable interfaces with the NCM523, a substantial fraction fail to maintain stability against LPSC. This trend aligns with the well-known chemical reactivity of sulfide-based SSEs, which possess a narrow ECW and readily react Li and transition metal species due to the high reactivity of sulfur. This behavior is also observed in LiNbO 3 , a widely used experimentally validated coating material, which also slightly exceeds the interfacial stability threshold with the LPSC. This result suggests that our cutoff standard is relatively conservative and reflects the stringent criteria used in our screening process. Therefore, the results of our interfacial stability analysis align with both theoretical predictions and experimentally observed trends. In addition, coating materials must exhibit sufficient electronic insulation properties to prevent the formation of undesired electronic conduction pathways during battery operation. This is essential for minimizing leakage current within the cell and ensuring long-term efficiency and stability. To assess this, we screened candidates using DFT-calculated band gap values retrieved from the MP database, as shown in Fig. 2 d. Since the PBE functional commonly used in DFT calculations tends to underestimate band gaps, we adopted a conservative threshold, considering only materials with a band gap greater than 2 eV as electronic insulators [ 59 ]. Based on this criterion, 150 coating candidates were identified as electronically insulated. This result suggests that most of materials previously screened for electrochemical and interfacial stability also possess desirable electronic insulation properties, further validating their suitability for practical application. While electrochemical, interfacial, and electronic stabilities are essential prerequisites for coating materials, Li-ion conductivity also plays a crucial role in facilitating efficient Li-ion exchange between the electrode and SSE, significantly impacting overall performance. Although DFT-based AIMD simulations can be used to evaluate ionic transport properties, their high computational cost renders them unsuitable for HTS of over 100 candidate structures. To overcome this limitation, we introduced a structure-based descriptor to enable a more efficient evaluation of Li-ion transport capability. Specifically, superior Li-ion conductivity is expected when Li–Li distances are shortened, facilitating the formation of extensive, interconnected Li-ion networks. To validate this, we analyzed the Li–Li networks in the crystal structures of well-known high ionic conductivity SSEs, such as LPSC, Li 7 La 3 Zr 2 O 12 (LLZO), and Li 10 GeP 2 S 12 (LGPS), and confirmed the presence of extensive Li–Li networks in all cases ( Fig. S2 ) [ 34 , 58 , 60 ]. Guided by these findings, candidate materials containing Li–Li connections shorter than 3.5 Å were screened, resulting in the identification of 88 structures. These materials are considered promising coating layers due to their potential to support efficient Li-ion transport at the cathode/electrolyte interface in mid-Ni ASSBs. Figure S3 summarizes the compositional histogram of candidate across the sequential screening steps. Initially, most structures contained metals (blue, purple, and orange); however, their numbers declined sharply in later stages, decreasing from 67, 85, and 83 to 21, 32, and 15, respectively. In contrast, metal-free compositions (green, red, and gray) were initially less abundant but preserved their numbers throughout the stages, changing slightly from 11, 6, and 13 to 8, 6, and 6. From these trends, it is evident that our screening workflow did not disproportionately eliminate any specific compositional category, as all categories retained at least five candidates in the final stage. This indicates that compositional diversity was broadly maintained throughout the screening process, despite the substantial reduction in total candidate count. 3.2. Investigation of Li-ion diffusion in rigorously filtered candidates From the prior screening steps, 88 oxide-based candidate structures were identified as promising coating materials based on the computational descriptors, as shown in Table S1 . Although these candidates are expected to exhibit favorable electrochemical and interfacial stability, practical applications in mid-Ni cathode systems require not only stability at high voltages (> 4 V) but also exceptional interfacial stability with both the NCM523 and SSE. Furthermore, since our earlier evaluation of Li-ion transport relied on structural descriptors rather than atomic-level dynamics, detailed Li-ion transport behavior should be examined through AIMD calculations. However, performing AIMD simulations on all 88 structures still poses a significant computational cost due to the large number of structures. To address this issue, we applied more rigorous screening criteria to the 88 identified candidates to narrow down the selection. Figure 3 a shows the crystal structures of 8 representative coating candidates that exhibit high-voltage stability (> 4 V) and good interfacial stability (> -50 meV/atom). Notably, this screening process successfully identified materials such as Li 3 B 11 O 18 , LiB 3 O 5 , Li 3 PO 4 , and LiMgPO 4 , which have previously been investigated as effective cathode coating materials [ 61 – 63 ]. This agreement with previous experimental findings strongly validates the rationality of our HTS approach. Furthermore, a large number of BO x and PO 4 containing compositions were observed, which can be attributed to the strong bonding tendencies of boron and phosphorus with oxygen. For these 8 representative candidates, comparison of their ECWs shows that all compositions exhibit wide stability ranges of approximately 2–4 V, indicating their suitability for operation in high-voltage systems, as illustrated in Fig. 3 b. Additionally, interfacial stability and reaction-product analysis confirm that these materials are chemically stable against both NCM523 and LPSC, as shown in Fig. 3 c and Tables S2 and S3 . These results demonstrate that our screening process effectively identifies coating materials that combine high-voltage electrochemical stability with strong interfacial compatibility. Following these analysis, AIMD simulations were conducted on 8 structures to verify their Li-ion mobility, as inferred from the Li–Li connectivity descriptor, over 200 ps at 1000 K. AIMD simulation serves as a powerful tool for dynamically evaluating Li-ion diffusivity at the atomic scale, particularly in SSEs. Fig. S4 indicates the mean squared displacement (MSD) results obtained from AIMD, which demonstrate that most candidates exhibit minimal Li-ion diffusion, as evidenced by the small MSD differences between Li and other atoms and their overall low displacements. (LiH 2 ClO was excluded due to the thermal instability of H atoms in H 2 O.) This result is attributed to the insufficient simulation timescale of 20 ps, which limited the observation of noticeable Li-ion transport in oxide-based materials. Despite these limitations, Li 3 Sc 2 (PO 4 ) 3 showed significantly higher Li-ion diffusivity than the other candidates, highlighting its strong potential as an effective Li-ion transport medium at the between electrode and electrolyte interface. Taken together, the results from both the HTS and detailed computational analyses identify Li 3 Sc 2 (PO 4 ) 3 as an ideal coating material, offering a well-balanced combination of electrochemical stability, interfacial stability, electronic property, and ionic mobility. 3.3. Exceptional Li-ion transport property and interfacial stability of Li 3 Sc 2 (PO 4 ) 3 As discussed in the previous section, a HTS approach was used to identify mid-Ni cathode coating materials that satisfy high-voltage electrochemical, interfacial stabilities with cathode and SSEs, electronic stability and superior ion mobility. As a result, we discovered that Li 3 Sc 2 (PO 4 ) 3 is a highly promising candidate, exhibiting superior Li-ion diffusivity along with enhanced properties compared to the other screened materials. While these findings confirm its potential as a coating material, further detailed analysis is essential to validate its practical performance as a mid-Ni cathode system. To this end, we reviewed the prior studies on the Li 3 Sc 2 (PO 4 ) 3 , finding that experimental investigation identified the α-, β-, and γ-phases in 1990 [ 64 ]. Among these phases, the γ-phase (the structure identified in our screening) was obtained by thermally treating the α-phase at 573 K. Furthermore, partial substitution with Ti or Zr has been confirmed to stabilize the γ-phase at room temperature while enabling high Li-ion conductivity [ 65 , 66 ]. These observations demonstrate that Li 3 Sc 2 (PO 4 ) 3 structures with enhanced ionic conductivity are experimentally accessible. A detailed comparison of the crystal structures, stability, and lattice parameters for the α-phase and γ-phase is presented in Figs. 4 a, b and Table S4 . (The β-phase was excluded due to its structural similarity to the α-phase.) Although previous HTS studies have identified Li 3 Sc 2 (PO 4 ) 3 as a promising candidate, they primarily relied on the γ-phases, often overlooking the structural distinctiveness of the experimentally synthesized phase [ 67 , 68 ]. To address this discrepancy and provide a comprehensive understanding, we compared the Li-ion mobility of the α- and γ-phases. While the previous AIMD simulations provided a preliminary evaluation of ion diffusion under a single temperature and short timescale, more detailed calculations are required for quantitative evaluation. Prior to performing such simulations, we conducted an analysis of the Li-ion transport network descriptor to estimate conductivity trends, using experimentally verified α-phase and γ-phase structure. As shown in Fig. S5 , the α-phase exhibits discontinuous Li-ion pathways, whereas the γ-phase clearly reveals two well-connected Li-ion networks. These observations suggest that the α-phase features limited Li-ion conduction, whereas the γ-phase provides well-connected transport pathways and are expected to exhibit superior Li-ion mobility. Based on these insights, extended AIMD simulations were carried out for these phases of Li 3 Sc 2 (PO 4 ) 3 at 900 K over 200 ps. Li-ion probability density analysis confirms that Li-ions in the α-phase exhibit severely restricted diffusion because its inherent Li–Li pathways are discontinuous (Fig. 4 c). Conversely, Li-ions in the γ-phase predominantly migrate along continuous Li–Li networks (Fig. 4 d). Furthermore, the MSD results for the α-phase (blue) also reveal confined Li-ion displacements, suggesting poor ionic mobility, as shown in Fig. 4 e. On the other hand, the γ-phase (red) exhibits a pronounced upward trend in MSD, demonstrating significantly enhanced Li-ion diffusion. These results align with the Li-ion networks analysis and experimental findings, confirming high Li-ion diffusivity in γ-phase. Building on these findings, we performed AIMD simulations for the α-phase and γ-phase at temperatures ranging from 800 K to 1200 K in 100 K intervals and estimated the ionic conductivity at 300 K using an Arrhenius relationship (Fig. 4 f). The γ-phase exhibits high ionic conductivity (0.2 mS/cm) compared to the α-phase structure (0.006 mS/cm). This performance exceeds available oxide-type SSEs, suggesting that Li 3 Sc 2 (PO 4 ) 3 holds significant potential not only as a protective coating layer [ 34 – 36 ]. These results demonstrate that Li 3 Sc 2 (PO 4 ) 3 offers a well-connected Li-ion transport network, enabling long-range diffusion and high ionic conductivity comparable to that of SSEs. Therefore, Li 3 Sc 2 (PO 4 ) 3 is considered an ideal coating candidate that satisfies the critical requirements of electrochemical, interfacial, electronic stabilities, and ionic conductivity. 3.4. Interface dynamics of SSE || Li 3 Sc 2 (PO 4 ) 3 || mid-Ni cathodes As discussed previous section, we demonstrated that Li 3 Sc 2 (PO 4 ) 3 exhibits well-balanced properties in terms of electrochemical, interfacial, electronic stabilities, and ionic conductivities, confirming its potential as a highly promising coating material. Despite these outstanding properties, practical application requires direct atomic-scale verification of the interfacial stability of Li 3 Sc 2 (PO 4 ) 3 against mid-Ni cathode and SSE. To directly evaluate this interfacial stability under realistic conditions, we constructed heterointerface structures consisting of NCM523, Li 3 Sc 2 (PO 4 ) 3 , and LPSC surfaces, and performed large-scale dynamic simulations. However, conventional DFT-based AIMD simulations poses significant computational challenges for such large interfacial systems due to their high atomic complexity and the resulting computational cost. To overcome this, we adopted a MLIP approach, which has recently gained significant attention for enabling large-scale simulations while retaining near-DFT accuracy. Among the various MLIPs, we used the SevenNet model, a graph-based pretrained uMLIP trained on extensive crystal structure datasets and DFT calculations, which have been benchmarked on the Matbench platform, demonstrating high predictive accuracy and computational efficiency [ 69 ]. Using the SevenNet uMLIP, we performed interfacial MD simulations to dynamically capture reaction products and structural evolution at the atomic scale. For model construction, we selected three distinct surfaces: the (104) surface of fully lithiated NCM523 ( Fig. S6 ), previously identified as the most stable configuration [ 70 , 71 ]; the (100) surface of LPSC, determined from our surface stability calculations ( Fig. S7 ); and the (101) surface of Li 3 Sc 2 (PO 4 ) 3 , chosen to minimize lattice mismatch along the a direction with the other two surfaces. The corresponding structural parameters of the interface models are detailed in Table S5 . All simulations were conducted for 500 ps, where the interfacial region within 20 Å of the center was performed under the NVE ensemble, while the surrounding bulk regions were maintained at 298 K under the NVT ensemble. To ensure large-scale modeling, each interface structure was modeled with over 1,000 atoms. Figure 5 a shows the uncoated interface between NCM523 and LPSC (100), where the MD simulations revealed significant PS 4 decomposition within the LPSC region. Detailed observations of the interfacial structure indicate that Ni from NCM523 migrate toward the electrolyte interact with sulfur in the PS 4 units. These results are consistent with previous experimental reports demonstrating Ni dissolution at NCM cathode/SSE interfaces [ 19 , 20 ]. Furthermore, sulfur released from decomposed PS 4 and single-sulfur species (Wyckoff position 4 a /4 c ) of LPSC, were found to form SO x compounds through bonding with oxygen in the NCM lattice. Therefore, these findings provide atomic-scale evidence that direct contact between NCM523 and LPSC leads to severe interfacial reactivity, resulting in extensive structural degradation involving nickel, oxygen, and PS 4 units. In contrast, the MD results for the Li 3 Sc 2 (PO 4 ) 3 -coated NCM523 interface demonstrate that both Li 3 Sc 2 (PO 4 ) 3 and NCM523 retained their structural integrity after 500 ps, as shown in Fig. 5 b. The detailed structure confirmed that the PO 4 tetrahedra and ScO 6 octahedra remained stable in interface, indicating negligible reactivity between the coating layer and the cathode. Similarly, the results for the Li 3 Sc 2 (PO 4 ) 3 || LPSC interface demonstrate that the coating layer remains intact after 500 ps, with the PS 4 units within LPSC preserved without decomposition (Fig. 5 c). In the interface region, Sc atoms at the Li 3 Sc 2 (PO 4 ) 3 surface form stable Sc–S bonds with sulfur atoms in PS 4 units, consistent with the reaction products shown in Table S3 . These interactions effectively suppress the decomposition of the LPSC framework and enhance interfacial stability. Taken together, these results offer direct dynamical evidence that Li 3 Sc 2 (PO 4 ) 3 effectively stabilizes both the mid-Ni cathode and LPSC at their interfaces, thereby serving as efficient protective coating material. The combined results from data-driven screening and dynamic interfacial simulations highlight Li 3 Sc 2 (PO 4 ) 3 as a practical and highly promising candidate for improving interfacial stability in next-generation ASSBs. 4. Conclusion In this work, we developed a data-driven high-throughput screening framework to identify oxide-based coating materials capable of stabilizing the interfaces in mid-Ni all-solid-state batteries (ASSBs). By integrating electrochemical stability windows, interfacial reaction energies, and Li-ion transport descriptors, thousands of oxide compositions were narrowed to eight promising candidates that meet stringent requirements for high-voltage operation and compatibility with both mid-Ni NCM and sulfide-based SSEs. Among these, Li 3 Sc 2 (PO 4 ) 3 consistently emerged as the most compelling material. DFT and AIMD calculations revealed a wide stability window above 4 V, strong interfacial compatibility, and a Li-ion conductivity of ~ 0.2 mS/cm–exceeding that of most oxide-type SSEs–enabled by a highly connected Li-ion migration network. Large-scale uMLIP simulations (for NCM523 || LPSC, NCM523 || Li 3 Sc 2 (PO 4 ) 3 , and Li 3 Sc 2 (PO 4 ) 3 || LPSC heterointerfaces) further showed that Li 3 Sc 2 (PO 4 ) 3 forms a stable interface with NCM523 and suppresses LPSC decomposition through preferential Sc–S bonding, elucidating the mechanism behind its interfacial robustness. Taken together, these results validate the effectiveness of our computational screening strategy for coating-material discovery and establish Li 3 Sc 2 (PO 4 ) 3 as a robust and multifunctional interfacial stabilizer for next-generation mid-Ni ASSBs. Beyond identifying a single material, this study demonstrates a generalizable pathway for accelerating interfacial-materials design by combining HTS methodologies, descriptor-based transport screening, and atomistic MLIP simulations. This integrated framework may be broadly applied for future discovery of protective layers in advanced solid-state battery chemistry. Declarations Acknowledgments Not applicable. Availability of data and material Raw data is available at: https://doi.org/10.6084/m9.figshare.30816767.v2. Competing interests The authors declare that they have no competing interests. Authors’ Information 1 School of Chemical Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea. 2 Department of Applied Chemistry, Hanyang University ERICA, Ansan 15588, Republic of Korea. 3 Center for Bionano Intelligence Education and Research, Hanyang University ERICA, Ansan 15588, Republic of Korea. 4 Department of Energy and Bio Sciences, Hanyang University ERICA, Ansan 15588, Republic of Korea. Funding This study was supported by grants from the Ministry of Trade, Industry and Energy (MOTIE) of Korea (P0022336 and RS-2024-00437260) Authors’ contributions Ji Hoon Kim: writing original draft, investigation, and validation. Seunghyun Lee: writing review, and funding acquisition. Sang Uck Lee: writing review & editing, project administration, supervision, and funding acquisition. All authors read and approved the final manuscript. References J.B. Goodenough, Y. Kim, Challenges for rechargeable Li batteries. Chem. Mater. 22 , 587–603 (2010). 10.1021/cm901452z B. 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Technol. 362 , 131708 (2025). 10.1016/j.seppur.2025.131708 Supplementary Files GA.png Graphical abstract Supplementaryinformation.pdf Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Minor revision 04 May, 2026 Reviewers agreed at journal 20 Apr, 2026 Reviewers invited by journal 20 Apr, 2026 Editor assigned by journal 18 Apr, 2026 First submitted to journal 17 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9450434","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":626665363,"identity":"5be0b7eb-0df5-461f-b374-1b62f27a0cdf","order_by":0,"name":"Ji Hoon Kim","email":"","orcid":"","institution":"Sungkyunkwan University - Natural Sciences Campus","correspondingAuthor":false,"prefix":"","firstName":"Ji","middleName":"Hoon","lastName":"Kim","suffix":""},{"id":626665364,"identity":"602ca3c1-ea2f-4295-9958-8180775726b4","order_by":1,"name":"Seunghyun Lee","email":"","orcid":"","institution":"Hanyang University - ERICA Campus","correspondingAuthor":false,"prefix":"","firstName":"Seunghyun","middleName":"","lastName":"Lee","suffix":""},{"id":626665365,"identity":"cea5adfc-7267-4fc7-9caf-d68251646302","order_by":2,"name":"Sang Uck Lee","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0ElEQVRIiWNgGAWjYFAC5gYgcYCBgb2BmRHEBLEJAEaoFp4DJGuRSCBSi/yMxMYHH2ruyOnOfP7YcGYbgxzfjQT8WgxuJDYbzjj2zNjsdo5x4sY2BmNJglokEtukeRsOJ267ncN88GEbQ+IGQlqADmv//bfhcP22m8cfg7TUE9TCcCOxDejtwwlmNxjADkswIOiwMw+bJXuOHTbcdibH2HDGOQnDmWceEHBYe/LBDz9qDsubHT/+WLKnzEae7zghh6EBCdKUj4JRMApGwSjADgD4k1DzVM6uJAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-9596-2349","institution":"Sungkyunkwan University - Natural Sciences Campus","correspondingAuthor":true,"prefix":"","firstName":"Sang","middleName":"Uck","lastName":"Lee","suffix":""}],"badges":[],"createdAt":"2026-04-17 14:50:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9450434/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9450434/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108121120,"identity":"8993cc7c-114c-420d-b46e-95b881a77ded","added_by":"auto","created_at":"2026-04-29 14:30:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":371962,"visible":true,"origin":"","legend":"\u003cp\u003eHierarchical computational screening workflow for discovering promising cathode coating materials. Candidates are sequentially down-selected based on a series of filtering criteria. The number of screened compositions at each stage is indicated alongside the corresponding process. The Materials Project version used in this study is 2025.02.12.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-9450434/v1/a2d35b4190b37f9d1b47312e.png"},{"id":108121117,"identity":"390b59c9-3fe5-4b25-9c95-d017091f70cc","added_by":"auto","created_at":"2026-04-29 14:30:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":394523,"visible":true,"origin":"","legend":"\u003cp\u003e(\u003cstrong\u003ea\u003c/strong\u003e) Electrochemical stability window of 4,634 screened materials. (\u003cstrong\u003eb\u003c/strong\u003e) Magnified view of the electrochemical stability region highlighted in green region in (a). (\u003cstrong\u003ec\u003c/strong\u003e) Interface reaction energy (∆E\u003csub\u003erxn\u003c/sub\u003e) of 265 candidate materials with both LPSC and NCM523. (\u003cstrong\u003ed\u003c/strong\u003e) Band gap of 154 screened compositions, grouped by their element categories. The green shaded regions in each panel indicate materials that passed the corresponding screening criteria. Blue, green, red, purple, orange, and gray circles represent materials containing metal (M), semi-metal (S), non-metal (N), metal + semi-metal (M+S), metal + non-mental (M+N), and semi-metal + non-metal (S+N), respectively, excluding Li and O.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-9450434/v1/1b9f2f796fc850f658cd6e11.png"},{"id":108182382,"identity":"0ce2d12e-458a-45ca-a71d-79ff9fccf694","added_by":"auto","created_at":"2026-04-30 08:59:20","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":583861,"visible":true,"origin":"","legend":"\u003cp\u003e(\u003cstrong\u003ea\u003c/strong\u003e) Crystal structures of 8 coating material candidates identified through high-throughput screening, along with their (\u003cstrong\u003eb\u003c/strong\u003e) electrochemical stability windows (vs. Li/Li\u003csup\u003e+\u003c/sup\u003e) and (\u003cstrong\u003ec\u003c/strong\u003e) interface stability with both NCM523 cathode and LPSC. ∆E\u003csub\u003erxn\u003c/sub\u003e values close to zero (green) indicate more stable interfaces.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-9450434/v1/11f0aeac679f67841e374416.png"},{"id":108182604,"identity":"89901215-52a3-4c60-b4be-0d66fdd7cfd6","added_by":"auto","created_at":"2026-04-30 08:59:27","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":660460,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e crystal structures: (a) α-phase (space group: p2\u003csub\u003e1\u003c/sub\u003e/c) and (b) γ-phase (space group: p2\u003csub\u003e1\u003c/sub\u003e/c). (c) Isosurface α-phase and (d) γ-phase for Li-ion probability density distribution at 900 K for obtained from AIMD simulation. (e) Li-ion MSD plot of according to two Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e phase. (f) Arrhenius plot of Li-ion diffusivities calculated from AIMD simulation in the temperature range of 800 – 1200 K, with extrapolation to estimate diffusivity at 300 K.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-9450434/v1/f44cf7c7379312b6256d2d36.png"},{"id":108121119,"identity":"96cf7208-e80d-45cc-a8cf-e5b3a1dcdd45","added_by":"auto","created_at":"2026-04-29 14:30:09","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":868703,"visible":true,"origin":"","legend":"\u003cp\u003eInterface modeling and MD simulation over 500 ps for (a) NCM523 (104) || LPSC (100), (b) NCM523 (104) || Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e (101), and (c) Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e (101) || LPSC (100) heterostructures. Top images show the initial interface models, middle images correspond to the structures after 500 ps of MD simulation, and bottom images display enlarged view of the interfacial regions.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-9450434/v1/0e2cc71577258cd85a0e571f.png"},{"id":108184708,"identity":"88c425ab-ba35-4082-96af-410be257163b","added_by":"auto","created_at":"2026-04-30 09:04:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3112645,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9450434/v1/db189c3f-f2ae-4593-9595-1338e0cd6c20.pdf"},{"id":108121114,"identity":"7cc768ac-2447-4fb6-9ef2-7b82809c6143","added_by":"auto","created_at":"2026-04-29 14:30:08","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":341450,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGraphical abstract\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"GA.png","url":"https://assets-eu.researchsquare.com/files/rs-9450434/v1/045f245ff3fe875f616786db.png"},{"id":108121115,"identity":"f5322727-0923-4848-8543-24e88028897e","added_by":"auto","created_at":"2026-04-29 14:30:08","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":2538425,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryinformation.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9450434/v1/884c3dfb177d33c64aabd618.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eHigh-Throughput Discovery of Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e as a Protective Coating for Stabilizing Mid-Ni NCM Interfaces in All-Solid-State Batteries\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe global transition toward carbon neutrality, combined with the rapid commercialization of electric vehicles (EVs), has significantly accelerated the demand for safer and cleaner energy storage technologies. Among the various options, lithium-ion batteries (LIBs) have emerged as the most promising technology due to their high energy density, long cycle life, and well-established manufacturing infrastructure [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, to meet the rigorous requirements of next-generation EVs, such as driving range of over 300 miles per charge, LIBs must continue to improve both performance and safety. Conventional LIBs typically used flammable organic liquid electrolytes, which introduce inherent safety risks, particularly under thermal runaway conditions [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The development of all-solid-state batteries (ASSBs) have gained widespread attention as a promising alternative by introducing inorganic solid-state electrolytes (SSEs), enabling improved safety and increase capacity without separator [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Furthermore, SSEs allow for the use of lithium metal anodes, offering the potential to significantly increase energy density. Beyond the benefits offered by SSEs, another common strategy to enhance the energy density of ASSBs is increasing the nickel content of cathode materials.\u003c/p\u003e \u003cp\u003eAmong the various components of ASSBs, the cathode plays a critical role in determining overall energy density and cycling performance. In particular, high-nickel (high-Ni) (Ni\u0026thinsp;\u0026ge;\u0026thinsp;80%) layered structures, such as LiNi\u003csub\u003e0.8\u003c/sub\u003eCo\u003csub\u003e0.1\u003c/sub\u003eMn\u003csub\u003e0.1\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e (NCM811), have been widely investigated due to their high specific capacity and reduced cobalt content [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Despite these notable advantages of high-Ni systems, these materials suffer from intrinsic limitations associated with their high-Ni content. As the nickel concentration increases, the cathode surface becomes significantly reactive, leading to irreversible phase transformation into a rock-salt structure and the release of lattice oxygen during delithiation [\u003cspan additionalcitationids=\"CR11 CR12 CR13\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. These degradation processes trigger structural instability, metal dissolution, and parasitic reactions, ultimately deteriorating battery performance and safety. Moreover, high-Ni cathodes are susceptible to the formation of residual lithium compounds and demonstrate poor interfacial compatibility with SSEs, further accelerating degradation over prolonged cycling [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn response to these issues and growing demands for cost reduction, mid-nickel (mid-Ni) layered oxide cathodes, containing approximately 50\u0026ndash;60% nickel such as LiNi\u003csub\u003e0.6\u003c/sub\u003eCo\u003csub\u003e0.2\u003c/sub\u003eMn\u003csub\u003e0.2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e (NCM622) and LiNi\u003csub\u003e0.5\u003c/sub\u003eCo\u003csub\u003e0.2\u003c/sub\u003eMn\u003csub\u003e0.3\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e (NCM523), have attracted renewed attention as more balanced alternative to high-Ni systems due to their optimal trade-off between energy density and structural stability [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The reduced nickel content mitigates surface reactivity, resulting in improved cycling stability and simultaneously contributes to a cost reduction. Although mid-Ni cathodes offer lower theoretical capacity compared to high-Ni counterparts, operating them at higher voltages (\u0026ge;\u0026thinsp;4.2 V) can compensate for the capacity loss, enabling them to meet the energy requirements of high-performance batteries [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Nevertheless, achieving stable high-voltage operation of mid-Ni cathodes in ASSBs remain challenges. At elevated voltages, mid-Ni are still vulnerable to surface degradation and interfacial side reactions with SSEs during extended cycling [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo this end, surface coating strategies have been extensively explored for numerous battery systems. Applying a protective coating layer to the cathode particles can physically separate the active material from the SSE, minimize undesired chemical reactions, and promote the formation of a robust and ionically conductive cathode\u0026ndash;electrolytes interphase. These coatings effectively reduce transition metal dissolution, oxygen loss, and structural decomposition under high-voltage operation, thereby improving long-term cycling performance [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. A wide range of coating materials including metals, semi-metals, and non-metals has been actively investigated, and many of them have demonstrated a significant ability to stabilize interface between the cathode and electrolyte [\u003cspan additionalcitationids=\"CR25 CR26 CR27 CR28\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. However, most reported coating materials to date are based on previously researched systems, and there remains a critical need to discover novel coating candidates specifically tailored for mid-Ni cathodes and stable operation under high-voltage conditions.\u003c/p\u003e \u003cp\u003eIn this context, computational high-throughput screening (HTS) approaches offer an efficient pathway to identify promising candidates across large material databases without relying on time-consuming experimental trial-and error. Such methods including density functional theory (DFT) enable rapid evaluation of electrochemical, interfacial compatibility, and ionic transport performance, resulting in accelerating the discovery of novel materials. These computational strategies have already been successfully applied not only to coating materials, but also across various functional domains, including oxide-based SSEs [\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHere, we conducted a data-driven computational HTS approach of oxide-based coating materials to identify novel candidates suitable for high-voltage mid-Ni cathodes. From materials project (MP) database [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], lithium- and oxygen- containing materials were evaluated using computational descriptors including electrochemical window (ECW), interfacial stability, band gap, and Li\u0026ndash;Li networks, leading to the identification of 88 screened candidates. Based on these candidates, 8 structures were further selected using strict criteria of high-voltage stability (\u0026gt;\u0026thinsp;4 V) and interfacial stability. Among these candidates, Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e exhibited outstanding properties, including electrochemical stability above 4 V, excellent interfacial compatibility with both the mid-Ni cathode and the Li\u003csub\u003e6\u003c/sub\u003ePS\u003csub\u003e5\u003c/sub\u003eCl (LPSC) SSE, a wide band gap, and high Li-ion diffusivity. To consider its experimentally observed structural forms, prior studies show that this composition exists in three experimental phases (α, β, and γ-phases). Notably, our ab initio molecular dynamics (AIMD) calculations demonstrate that the γ-phase (the structure identified in our screening) exhibits superior ionic conductivity (~\u0026thinsp;0.2 mS/cm), exceeding that of most oxide-type SSEs [\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. This superior ionic conductivity was further supported by probability density analysis, which revealed a well-defined Li-ion diffusion pathway. To further evaluate interfacial stability, 500 ps molecular dynamics (MD) simulations of the cathode/LPSC interface were carried out using a universal machine-learning interatomic potential (uMLIP). The results demonstrate that direct contact between NCM523 and LPSC leads to PS\u003csub\u003e4\u003c/sub\u003e decomposition in LPSC and nickel dissolution into the electrolyte, which destabilizes the interfacial structure. In contrast, introducing Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e as a coating layer results in minimal reaction products, a stable interface, and suppressed PS\u003csub\u003e4\u003c/sub\u003e decomposition within the bulk region. Based on these superior properties, Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e is expected to serve as an effective coating material for mid-Ni cathodes. These results highlight the importance of systematic computational materials design in next-generation ASSBs, particularly by enabling the discovery of effective coating materials that stabilize the interface between SSEs and mid-Ni cathodes.\u003c/p\u003e"},{"header":"2. Computational details","content":"\u003cp\u003eAll DFT calculations and MD simulations were performed with the Vienna \u003cem\u003eab initio\u003c/em\u003e simulation package (VASP 5.4.4) [\u003cspan additionalcitationids=\"CR38 CR39\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] and a large-scale atomic/molecular massively parallel simulator (LAMMPS) [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] package, respectively. Structural optimization was conducted using the projector augmented wave (PAW) [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e] method and the Perdew-Burke-Ernzerohf (PBE) generalized gradient approximation (GGA) [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] functional. Lattice constants and internal atomic positions were fully relaxed until the residual forces reached\u0026thinsp;\u0026lt;\u0026thinsp;0.04 eV/\u0026Aring;. Spin-polarized calculations were performed for systems containing 3d transition metals. The AIMD simulations were performed with an NVT Nose-Hoover thermostat [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] for the fully relaxed geometry to obtain Li-ion diffusivity during 20 ps at 1000 K. The simulation parameters (cell size, spin, and simulation temperatures) were adopted from our previous work [\u003cspan additionalcitationids=\"CR48\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Additional AIMD simulation were carried out from 900 K to 1200 K in 100 K intervals to estimate Li-ion conductivity at room temperature using an Arrhenius extrapolation. A gamma-centered 1 \u0026times; 1 \u0026times; 1 \u003cem\u003ek\u003c/em\u003e-point mesh and a time step of 2 fs were used. Details of the procedure to obtain \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\sigma\\:}_{RT}\\)\u003c/span\u003e\u003c/span\u003e are described in supplementary information. All structures, reference formation energies, and bandgap were obtained from the MP database [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. ECW was evaluated using the grand potential phase diagram approach, in which the stability of each compound was assessed as a function of lithium chemical potential [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Phase stability was determined by constructing convex hulls in the relevant chemical spaces and calculating the energy above hull for each compound based on the same database [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Further details of these calculations are provided in supplementary information. Among the various types of machine-learning interatomic potentials (MLIPs), the Scalable EquiVariance-Enabled Neural Network (SevenNet) was selected to perform MD simulations using the \u003cem\u003e7\u003c/em\u003enet-0 pretrained model with LAMMPS [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e"},{"header":"3. Results and discussion","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1. High-throughput screening of cathode coating oxide materials\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIdeal coating materials for ASSBs must meet multiple stringent criteria, such as electrochemical stability, efficient ionic transport, and interfacial compatibility with both electrodes and SSEs. These requirements become particularly important for mid-Ni cathodes due to their relatively high operating voltages, which are essential to maintain equivalent energy density compared to high-Ni cathode. Consequently, the pool of viable coating materials is severely limited, making it difficult to identify candidates that simultaneously fulfill all critical properties.\u003c/p\u003e \u003cp\u003eTo overcome this, we adopted a HTS approach aimed at theoretically discovering promising coating materials for stabilizing the interface between mid-Ni cathodes and SSEs in ASSBs. HTS enables the rapid and consistent discovery of new materials by using clearly defined property criteria, offering a systematic and reproducible way that is especially effective in theoretical computational research due to its uniform evaluation standards. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the overall HTS workflow used in this study. To discover novel coating materials, we systematically conducted a top-down screening process to evaluate electrochemical, interfacial, electronic stabilities, and ionic transport properties across an extensive dataset. This approach enabled the identification of several candidates that satisfied all targeted criteria, and Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e emerged as the most favorable material in the final screening stage.\u003c/p\u003e \u003cp\u003eInitially, the early-stage dataset was constructed by retrieving 17,230 Li- and O- containing oxide crystal structures from the MP database. Oxide-based materials were selected due to their intrinsic high electrochemical stability and established use in various coating applications. For a more detailed understanding of compositional trends, we categorized the retained compounds according to the type of composed elements excluding Li and O (metals, metalloids(semi-metals), non-metals, and radioactive elements), as summarized in \u003cb\u003eFig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e. To refine these datasets, we excluded structures containing radioactive elements or featuring more than two additional elements beyond Li and O. Among candidates with identical compositions, only the structure with the lowest formation energy was selected to represent that composition, ensuring focus on thermodynamically stable phases. Through this filtering process, we finalized a screening pool of 4,634 structures. These preprocessing steps were critical not only for enhancing the efficiency of the HTS process but also for prioritizing materials with greater experimental feasibility.\u003c/p\u003e \u003cp\u003eConsidering the harsh battery operating conditions, coating materials should possess intrinsic electrochemical stability, characterized by a wide ECW that ensures resistance to decomposition under both oxidative and reductive environments. In this regard, we calculated the theoretical ECW for each candidate materials. By applying cutoff criteria of oxidation voltage above 3.5 V and reduction voltage below 2 V, a total of 265 materials were identified as electrochemically stable. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea clearly demonstrates that although many materials satisfy either the oxidative or reductive stability conditions, only a limited subset fulfills both simultaneously. This subset encompasses not only widely adopted coating materials such as Li\u003csub\u003e3\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e, LiNbO\u003csub\u003e3\u003c/sub\u003e, and LiAlO\u003csub\u003e2\u003c/sub\u003e but also high-voltage candidates like LiRb\u003csub\u003e2\u003c/sub\u003eAsO\u003csub\u003e4\u003c/sub\u003e, which withstands potentials up to 6.5 V as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb [\u003cspan additionalcitationids=\"CR55\" citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Moreover, Li\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e, a known product of solid electrolyte interphase (SEI) formation, was also included among the screened candidates. Its presence supports the interpretation that the SEI layer forms spontaneously due to its inherent electrochemical stability [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. These findings indicate that our ECW-based filtering approach is both theoretical and experimental reasonable observation, demonstrating its reliability for discovering stable coating materials.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWhile electrochemical stability is a critical prerequisite, coating materials must also demonstrate robust interfacial stability with both the cathode and SSEs. An ideal coating material must prevent direct chemical reactions between the cathode and electrolyte, while simultaneously allowing efficient Li-ion transport across the interface. To evaluate this requirement, we assessed the interfacial reaction energies (∆E\u003csub\u003erxn\u003c/sub\u003e) between each screened candidate and both the cathode and the SSE. NCM523 and LPSC were selected as representative materials of a layered mid-Ni cathode and SSE with high ionic conductivity, respectively [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Adopting the criterion established in previous research, we regarded candidates with ∆E\u003csub\u003erxn\u003c/sub\u003e \u0026ge; \u0026minus;\u0026thinsp;100 meV/atom as interracially compatible with both NCM523 and LPSC [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec, a total of 154 materials satisfy this threshold, representing approximately a 50% reduction from the previous screening step and highlighting the stringency of the applied criterion. Notably, while many materials exhibited stable interfaces with the NCM523, a substantial fraction fail to maintain stability against LPSC. This trend aligns with the well-known chemical reactivity of sulfide-based SSEs, which possess a narrow ECW and readily react Li and transition metal species due to the high reactivity of sulfur. This behavior is also observed in LiNbO\u003csub\u003e3\u003c/sub\u003e, a widely used experimentally validated coating material, which also slightly exceeds the interfacial stability threshold with the LPSC. This result suggests that our cutoff standard is relatively conservative and reflects the stringent criteria used in our screening process. Therefore, the results of our interfacial stability analysis align with both theoretical predictions and experimentally observed trends.\u003c/p\u003e \u003cp\u003eIn addition, coating materials must exhibit sufficient electronic insulation properties to prevent the formation of undesired electronic conduction pathways during battery operation. This is essential for minimizing leakage current within the cell and ensuring long-term efficiency and stability. To assess this, we screened candidates using DFT-calculated band gap values retrieved from the MP database, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed. Since the PBE functional commonly used in DFT calculations tends to underestimate band gaps, we adopted a conservative threshold, considering only materials with a band gap greater than 2 eV as electronic insulators [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Based on this criterion, 150 coating candidates were identified as electronically insulated. This result suggests that most of materials previously screened for electrochemical and interfacial stability also possess desirable electronic insulation properties, further validating their suitability for practical application.\u003c/p\u003e \u003cp\u003eWhile electrochemical, interfacial, and electronic stabilities are essential prerequisites for coating materials, Li-ion conductivity also plays a crucial role in facilitating efficient Li-ion exchange between the electrode and SSE, significantly impacting overall performance. Although DFT-based AIMD simulations can be used to evaluate ionic transport properties, their high computational cost renders them unsuitable for HTS of over 100 candidate structures. To overcome this limitation, we introduced a structure-based descriptor to enable a more efficient evaluation of Li-ion transport capability. Specifically, superior Li-ion conductivity is expected when Li\u0026ndash;Li distances are shortened, facilitating the formation of extensive, interconnected Li-ion networks. To validate this, we analyzed the Li\u0026ndash;Li networks in the crystal structures of well-known high ionic conductivity SSEs, such as LPSC, Li\u003csub\u003e7\u003c/sub\u003eLa\u003csub\u003e3\u003c/sub\u003eZr\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e12\u003c/sub\u003e (LLZO), and Li\u003csub\u003e10\u003c/sub\u003eGeP\u003csub\u003e2\u003c/sub\u003eS\u003csub\u003e12\u003c/sub\u003e (LGPS), and confirmed the presence of extensive Li\u0026ndash;Li networks in all cases (\u003cb\u003eFig. S2\u003c/b\u003e) [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Guided by these findings, candidate materials containing Li\u0026ndash;Li connections shorter than 3.5 \u0026Aring; were screened, resulting in the identification of 88 structures. These materials are considered promising coating layers due to their potential to support efficient Li-ion transport at the cathode/electrolyte interface in mid-Ni ASSBs.\u003c/p\u003e \u003cp\u003eFigure S3 summarizes the compositional histogram of candidate across the sequential screening steps. Initially, most structures contained metals (blue, purple, and orange); however, their numbers declined sharply in later stages, decreasing from 67, 85, and 83 to 21, 32, and 15, respectively. In contrast, metal-free compositions (green, red, and gray) were initially less abundant but preserved their numbers throughout the stages, changing slightly from 11, 6, and 13 to 8, 6, and 6. From these trends, it is evident that our screening workflow did not disproportionately eliminate any specific compositional category, as all categories retained at least five candidates in the final stage. This indicates that compositional diversity was broadly maintained throughout the screening process, despite the substantial reduction in total candidate count.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Investigation of Li-ion diffusion in rigorously filtered candidates\u003c/h2\u003e \u003cp\u003eFrom the prior screening steps, 88 oxide-based candidate structures were identified as promising coating materials based on the computational descriptors, as shown in \u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e. Although these candidates are expected to exhibit favorable electrochemical and interfacial stability, practical applications in mid-Ni cathode systems require not only stability at high voltages (\u0026gt;\u0026thinsp;4 V) but also exceptional interfacial stability with both the NCM523 and SSE. Furthermore, since our earlier evaluation of Li-ion transport relied on structural descriptors rather than atomic-level dynamics, detailed Li-ion transport behavior should be examined through AIMD calculations. However, performing AIMD simulations on all 88 structures still poses a significant computational cost due to the large number of structures.\u003c/p\u003e \u003cp\u003eTo address this issue, we applied more rigorous screening criteria to the 88 identified candidates to narrow down the selection. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea shows the crystal structures of 8 representative coating candidates that exhibit high-voltage stability (\u0026gt;\u0026thinsp;4 V) and good interfacial stability (\u0026gt; -50 meV/atom). Notably, this screening process successfully identified materials such as Li\u003csub\u003e3\u003c/sub\u003eB\u003csub\u003e11\u003c/sub\u003eO\u003csub\u003e18\u003c/sub\u003e, LiB\u003csub\u003e3\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e, Li\u003csub\u003e3\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e, and LiMgPO\u003csub\u003e4\u003c/sub\u003e, which have previously been investigated as effective cathode coating materials [\u003cspan additionalcitationids=\"CR62\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. This agreement with previous experimental findings strongly validates the rationality of our HTS approach. Furthermore, a large number of BO\u003csub\u003ex\u003c/sub\u003e and PO\u003csub\u003e4\u003c/sub\u003e containing compositions were observed, which can be attributed to the strong bonding tendencies of boron and phosphorus with oxygen.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor these 8 representative candidates, comparison of their ECWs shows that all compositions exhibit wide stability ranges of approximately 2\u0026ndash;4 V, indicating their suitability for operation in high-voltage systems, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb. Additionally, interfacial stability and reaction-product analysis confirm that these materials are chemically stable against both NCM523 and LPSC, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec and \u003cb\u003eTables S2\u003c/b\u003e and \u003cb\u003eS3\u003c/b\u003e. These results demonstrate that our screening process effectively identifies coating materials that combine high-voltage electrochemical stability with strong interfacial compatibility.\u003c/p\u003e \u003cp\u003eFollowing these analysis, AIMD simulations were conducted on 8 structures to verify their Li-ion mobility, as inferred from the Li\u0026ndash;Li connectivity descriptor, over 200 ps at 1000 K. AIMD simulation serves as a powerful tool for dynamically evaluating Li-ion diffusivity at the atomic scale, particularly in SSEs. \u003cb\u003eFig. S4\u003c/b\u003e indicates the mean squared displacement (MSD) results obtained from AIMD, which demonstrate that most candidates exhibit minimal Li-ion diffusion, as evidenced by the small MSD differences between Li and other atoms and their overall low displacements. (LiH\u003csub\u003e2\u003c/sub\u003eClO was excluded due to the thermal instability of H atoms in H\u003csub\u003e2\u003c/sub\u003eO.) This result is attributed to the insufficient simulation timescale of 20 ps, which limited the observation of noticeable Li-ion transport in oxide-based materials. Despite these limitations, Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e showed significantly higher Li-ion diffusivity than the other candidates, highlighting its strong potential as an effective Li-ion transport medium at the between electrode and electrolyte interface. Taken together, the results from both the HTS and detailed computational analyses identify Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e as an ideal coating material, offering a well-balanced combination of electrochemical stability, interfacial stability, electronic property, and ionic mobility.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Exceptional Li-ion transport property and interfacial stability of Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs discussed in the previous section, a HTS approach was used to identify mid-Ni cathode coating materials that satisfy high-voltage electrochemical, interfacial stabilities with cathode and SSEs, electronic stability and superior ion mobility. As a result, we discovered that Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e is a highly promising candidate, exhibiting superior Li-ion diffusivity along with enhanced properties compared to the other screened materials. While these findings confirm its potential as a coating material, further detailed analysis is essential to validate its practical performance as a mid-Ni cathode system. To this end, we reviewed the prior studies on the Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e, finding that experimental investigation identified the α-, β-, and γ-phases in 1990 [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Among these phases, the γ-phase (the structure identified in our screening) was obtained by thermally treating the α-phase at 573 K. Furthermore, partial substitution with Ti or Zr has been confirmed to stabilize the γ-phase at room temperature while enabling high Li-ion conductivity [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. These observations demonstrate that Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e structures with enhanced ionic conductivity are experimentally accessible. A detailed comparison of the crystal structures, stability, and lattice parameters for the α-phase and γ-phase is presented in Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, b and \u003cb\u003eTable S4\u003c/b\u003e. (The β-phase was excluded due to its structural similarity to the α-phase.) Although previous HTS studies have identified Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e as a promising candidate, they primarily relied on the γ-phases, often overlooking the structural distinctiveness of the experimentally synthesized phase [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. To address this discrepancy and provide a comprehensive understanding, we compared the Li-ion mobility of the α- and γ-phases.\u003c/p\u003e \u003cp\u003eWhile the previous AIMD simulations provided a preliminary evaluation of ion diffusion under a single temperature and short timescale, more detailed calculations are required for quantitative evaluation. Prior to performing such simulations, we conducted an analysis of the Li-ion transport network descriptor to estimate conductivity trends, using experimentally verified α-phase and γ-phase structure. As shown in \u003cb\u003eFig. S5\u003c/b\u003e, the α-phase exhibits discontinuous Li-ion pathways, whereas the γ-phase clearly reveals two well-connected Li-ion networks. These observations suggest that the α-phase features limited Li-ion conduction, whereas the γ-phase provides well-connected transport pathways and are expected to exhibit superior Li-ion mobility. Based on these insights, extended AIMD simulations were carried out for these phases of Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e at 900 K over 200 ps. Li-ion probability density analysis confirms that Li-ions in the α-phase exhibit severely restricted diffusion because its inherent Li\u0026ndash;Li pathways are discontinuous (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). Conversely, Li-ions in the γ-phase predominantly migrate along continuous Li\u0026ndash;Li networks (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed). Furthermore, the MSD results for the α-phase (blue) also reveal confined Li-ion displacements, suggesting poor ionic mobility, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee. On the other hand, the γ-phase (red) exhibits a pronounced upward trend in MSD, demonstrating significantly enhanced Li-ion diffusion. These results align with the Li-ion networks analysis and experimental findings, confirming high Li-ion diffusivity in γ-phase. Building on these findings, we performed AIMD simulations for the α-phase and γ-phase at temperatures ranging from 800 K to 1200 K in 100 K intervals and estimated the ionic conductivity at 300 K using an Arrhenius relationship (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ef). The γ-phase exhibits high ionic conductivity (0.2 mS/cm) compared to the α-phase structure (0.006 mS/cm). This performance exceeds available oxide-type SSEs, suggesting that Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e holds significant potential not only as a protective coating layer [\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. These results demonstrate that Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e offers a well-connected Li-ion transport network, enabling long-range diffusion and high ionic conductivity comparable to that of SSEs. Therefore, Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e is considered an ideal coating candidate that satisfies the critical requirements of electrochemical, interfacial, electronic stabilities, and ionic conductivity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Interface dynamics of SSE || Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e || mid-Ni cathodes\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs discussed previous section, we demonstrated that Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e exhibits well-balanced properties in terms of electrochemical, interfacial, electronic stabilities, and ionic conductivities, confirming its potential as a highly promising coating material. Despite these outstanding properties, practical application requires direct atomic-scale verification of the interfacial stability of Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e against mid-Ni cathode and SSE. To directly evaluate this interfacial stability under realistic conditions, we constructed heterointerface structures consisting of NCM523, Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e, and LPSC surfaces, and performed large-scale dynamic simulations.\u003c/p\u003e \u003cp\u003eHowever, conventional DFT-based AIMD simulations poses significant computational challenges for such large interfacial systems due to their high atomic complexity and the resulting computational cost. To overcome this, we adopted a MLIP approach, which has recently gained significant attention for enabling large-scale simulations while retaining near-DFT accuracy. Among the various MLIPs, we used the SevenNet model, a graph-based pretrained uMLIP trained on extensive crystal structure datasets and DFT calculations, which have been benchmarked on the Matbench platform, demonstrating high predictive accuracy and computational efficiency [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. Using the SevenNet uMLIP, we performed interfacial MD simulations to dynamically capture reaction products and structural evolution at the atomic scale. For model construction, we selected three distinct surfaces: the (104) surface of fully lithiated NCM523 (\u003cb\u003eFig. S6\u003c/b\u003e), previously identified as the most stable configuration [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]; the (100) surface of LPSC, determined from our surface stability calculations (\u003cb\u003eFig. S7\u003c/b\u003e); and the (101) surface of Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e, chosen to minimize lattice mismatch along the a direction with the other two surfaces. The corresponding structural parameters of the interface models are detailed in \u003cb\u003eTable S5\u003c/b\u003e. All simulations were conducted for 500 ps, where the interfacial region within 20 \u0026Aring; of the center was performed under the NVE ensemble, while the surrounding bulk regions were maintained at 298 K under the NVT ensemble. To ensure large-scale modeling, each interface structure was modeled with over 1,000 atoms.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea shows the uncoated interface between NCM523 and LPSC (100), where the MD simulations revealed significant PS\u003csub\u003e4\u003c/sub\u003e decomposition within the LPSC region. Detailed observations of the interfacial structure indicate that Ni from NCM523 migrate toward the electrolyte interact with sulfur in the PS\u003csub\u003e4\u003c/sub\u003e units. These results are consistent with previous experimental reports demonstrating Ni dissolution at NCM cathode/SSE interfaces [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Furthermore, sulfur released from decomposed PS\u003csub\u003e4\u003c/sub\u003e and single-sulfur species (Wyckoff position 4\u003cem\u003ea\u003c/em\u003e/4\u003cem\u003ec\u003c/em\u003e) of LPSC, were found to form SO\u003csub\u003ex\u003c/sub\u003e compounds through bonding with oxygen in the NCM lattice. Therefore, these findings provide atomic-scale evidence that direct contact between NCM523 and LPSC leads to severe interfacial reactivity, resulting in extensive structural degradation involving nickel, oxygen, and PS\u003csub\u003e4\u003c/sub\u003e units.\u003c/p\u003e \u003cp\u003eIn contrast, the MD results for the Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e-coated NCM523 interface demonstrate that both Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e and NCM523 retained their structural integrity after 500 ps, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb. The detailed structure confirmed that the PO\u003csub\u003e4\u003c/sub\u003e tetrahedra and ScO\u003csub\u003e6\u003c/sub\u003e octahedra remained stable in interface, indicating negligible reactivity between the coating layer and the cathode. Similarly, the results for the Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e || LPSC interface demonstrate that the coating layer remains intact after 500 ps, with the PS\u003csub\u003e4\u003c/sub\u003e units within LPSC preserved without decomposition (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). In the interface region, Sc atoms at the Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e surface form stable Sc\u0026ndash;S bonds with sulfur atoms in PS\u003csub\u003e4\u003c/sub\u003e units, consistent with the reaction products shown in \u003cb\u003eTable S3\u003c/b\u003e. These interactions effectively suppress the decomposition of the LPSC framework and enhance interfacial stability.\u003c/p\u003e \u003cp\u003eTaken together, these results offer direct dynamical evidence that Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e effectively stabilizes both the mid-Ni cathode and LPSC at their interfaces, thereby serving as efficient protective coating material. The combined results from data-driven screening and dynamic interfacial simulations highlight Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e as a practical and highly promising candidate for improving interfacial stability in next-generation ASSBs.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eIn this work, we developed a data-driven high-throughput screening framework to identify oxide-based coating materials capable of stabilizing the interfaces in mid-Ni all-solid-state batteries (ASSBs). By integrating electrochemical stability windows, interfacial reaction energies, and Li-ion transport descriptors, thousands of oxide compositions were narrowed to eight promising candidates that meet stringent requirements for high-voltage operation and compatibility with both mid-Ni NCM and sulfide-based SSEs.\u003c/p\u003e \u003cp\u003eAmong these, Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e consistently emerged as the most compelling material. DFT and AIMD calculations revealed a wide stability window above 4 V, strong interfacial compatibility, and a Li-ion conductivity of ~\u0026thinsp;0.2 mS/cm\u0026ndash;exceeding that of most oxide-type SSEs\u0026ndash;enabled by a highly connected Li-ion migration network. Large-scale uMLIP simulations (for NCM523 || LPSC, NCM523 || Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e, and Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e || LPSC heterointerfaces) further showed that Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e forms a stable interface with NCM523 and suppresses LPSC decomposition through preferential Sc\u0026ndash;S bonding, elucidating the mechanism behind its interfacial robustness.\u003c/p\u003e \u003cp\u003eTaken together, these results validate the effectiveness of our computational screening strategy for coating-material discovery and establish Li\u003csub\u003e3\u003c/sub\u003eSc\u003csub\u003e2\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e as a robust and multifunctional interfacial stabilizer for next-generation mid-Ni ASSBs. Beyond identifying a single material, this study demonstrates a generalizable pathway for accelerating interfacial-materials design by combining HTS methodologies, descriptor-based transport screening, and atomistic MLIP simulations. This integrated framework may be broadly applied for future discovery of protective layers in advanced solid-state battery chemistry.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRaw data is available at: https://doi.org/10.6084/m9.figshare.30816767.v2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e School of Chemical Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003e Department of Applied Chemistry, Hanyang University ERICA, Ansan 15588, Republic of Korea.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003e Center for Bionano Intelligence Education and Research, Hanyang University ERICA, Ansan 15588, Republic of Korea.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e4\u003c/sup\u003e Department of Energy and Bio Sciences, Hanyang University ERICA, Ansan 15588, Republic of Korea.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by grants from the Ministry of Trade, Industry and Energy (MOTIE) of Korea (P0022336 and RS-2024-00437260)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJi Hoon Kim: writing original draft, investigation, and validation. 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Technol. \u003cb\u003e362\u003c/b\u003e, 131708 (2025). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.seppur.2025.131708\u003c/span\u003e\u003cspan address=\"10.1016/j.seppur.2025.131708\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nano-convergence","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ncon","sideBox":"Learn more about [Nano Convergence](https://www.springer.com/journal/40580)","snPcode":"40580","submissionUrl":"https://www.editorialmanager.com/ncon/default2.aspx","title":"Nano Convergence","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Mid-nickel cathode, High-throughput screening (HTS), Coating materials, Density functional theory (DFT), and Machine learning interatomic potential (MLIP)","lastPublishedDoi":"10.21203/rs.3.rs-9450434/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9450434/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"As all-solid-state battery (ASSB) technologies continue to advance, interest has resurfaced in mid-nickel (mid-Ni) LiNiCoMnO (NCM; x\u0026thinsp;=\u0026thinsp;0.5) cathodes due to their enhanced structural stability, reduced oxygen evolution, and higher capacities at elevated cutoff voltages compared to high-nickel compositions. However, interfacial degradation including parasitic reactions with solid-state electrolytes (SSEs) remains a major challenge. To address this issue, we conducted a high-throughput computational screening of oxide-based coating materials, evaluating their electrochemical stability, interfacial robustness, and Li-ion conductivity using Li\u0026ndash;Li network descriptors. From this screening, 8 candidates were selected based on strict criteria. Among them, LiSc(PO) emerged as a particularly promising coating material, exhibiting strong electrochemical stability under high-voltage conditions (\u0026gt;\u0026thinsp;4 V) and substantial ionic conductivity (0.2 mS/cm), exceeding that of most oxide-type SSEs, as confirmed by ab initio molecular dynamics (AIMD) simulations. Furthermore, large-scale molecular dynamics simulations using a universal machine-learning interatomic potential (uMLIP) demonstrate its ability to suppress surface degradation of mid-Ni NCM and prevent [PS] decomposition in LiPSCl, confirming its potential as a protective coating. These findings highlight the effectiveness of our computational screening strategy for coating-material discovery and underscore the potential of LiSc(PO) as a robust interfacial layer for stabilizing mid-Ni ASSBs.","manuscriptTitle":"High-Throughput Discovery of Li3Sc2(PO4)3 as a Protective Coating for Stabilizing Mid-Ni NCM Interfaces in All-Solid-State Batteries","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-29 14:30:04","doi":"10.21203/rs.3.rs-9450434/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor revision","date":"2026-05-04T12:07:28+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2026-04-21T02:10:01+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-21T02:09:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-18T15:51:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"Nano Convergence","date":"2026-04-17T10:49:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nano-convergence","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ncon","sideBox":"Learn more about [Nano Convergence](https://www.springer.com/journal/40580)","snPcode":"40580","submissionUrl":"https://www.editorialmanager.com/ncon/default2.aspx","title":"Nano Convergence","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cc497bfc-2637-4382-9ca7-0035a14d4fc2","owner":[],"postedDate":"April 29th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Minor revision","date":"2026-05-04T12:07:28+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T10:58:00+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-29 14:30:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9450434","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9450434","identity":"rs-9450434","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}