Author: H.Kim†, I.Kim†, J.Kim, C.Kim, M.So, J.Kim*Title: Machine learning–driven design of cost-effective cutting tools: Composition optimization of transition-metal-doped WCJournal: International Journal of Refractory Metals and Hard MaterialsYear: 2026Impact factor: 4.7Abstract:In this study, we developed a machine learning (ML) framework based on 174 density functional theory (DFT)-calculated data points to predict the elastic properties of WC systems doped with 10 transition metals. A set of 13 descriptors, including valence electron concentration (VEC) and melting temperature (MT), were constructed and reduced to 8 non-redundant features. Among the models tested, Gradient Boosting achieved the best performance for bulk modulus (R2 = 0.932), while Random Forest showed the highest accuracy for shear modulus (R2 = 0.931). Shapley Additive exPlanations (SHAP) analysis identified VEC, MT, and electronegativity as key factors governing elastic behavior. Using the trained models, high-throughput screening of 1710 compositions revealed that Re doping dominates stiffness enhancement, with (W0.75Re0.25)C exhibiting the highest predicted performance (B = 397.5 GPa, G = 292.7 GPa). In addition, dual-doping strategies combining Re with other transition metals effectively reduced Re content while maintaining near-optimal properties. Furthermore, Re/Ru-free compositions such as (W0.917Cr0.056Mo0.028)C, (W0.889Cr0.111)C, and (W0.917Cr0.083)C achieved competitive performance (B > 380 GPa), suggesting viable cost-effective alternatives. These results demonstrate that ML-based screening can cost-effectively accelerate the design of high-performance WC-based carbides.

Author: Nilüfer Çakmakçı Lee†, J.Lee, J.Choi, I.Bae, J.Bang, H.Kim, D.Lee, J.Han, J.Kwak, J.Kim*, Y.Jeong*Title: Equal mass, unequal impact: Particle density and bending rigidity of carbon nanotube additives govern silicon anode performanceJournal: Journal of Power SourcesYear: 2026Impact factor: 8.4Abstract:Silicon offers a much higher lithium storage capacity than graphite but suffers from severe volume expansion during cycling, which undermines electrode stability. Carbon nanotubes (CNTs) are widely employed to address this limitation, yet their coupled mechanical and electrical functions remain poorly understood. Here, we systematically compare single-walled (SWCNT) and multi-walled (MWCNT) carbon nanotubes as conductive additives in silicon nanoparticle anodes at identical loadings (0.5–5 wt%). SWCNTs are theoretically estimated to provide over 103 times more individual tubes per gram, forming dense percolation networks that enable rapid charge–discharge performance (2330 mAh g−1 at 3 C, 5 wt%). MWCNTs, though fewer in number, exhibit higher bending rigidity, restricting electrode thickening to ∼50% after 10 cycles. At CNT contents below 1 wt%, capacity retention scales with particle population, emphasizing the dominance of physical contact over intrinsic conductivity. These results decouple the roles of particle density (SWCNT) and mechanical stiffness (MWCNT), offering practical guidelines for optimizing CNT selection in cost-effective, high-energy silicon anodes.

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Author: H.Kim†, I.Bae†, J.Kwak, H.Son, J.Kim*Title: Oxygen incorporation in Ti2AlC MAX phases as bond coats: Multi-scale simulations for enhanced thermal shock resistanceJournal: Journal of Materials Research and TechnologyYear: 2026Impact factor: 6.6Abstract:In thermal barrier coating (TBC) systems, MAX phases have emerged as potential alternatives to conventional metallic bond coats (BCs). Using multi-scale simulations, we examined how oxygen incorporation affects the high-temperature behavior of Ti2AlC. Although oxygen is typically considered harmful in BCs, Ti2Al(C1-xOx) showed different results that moderate oxygen incorporation lowers Young's modulus and increases the thermal expansion coefficient. This oxygen-induced softening effectively mitigates the large stiffness and thermal-expansion between the ceramic top coat and the superalloy substrate, thereby reducing thermal stress. Comparisons with CoNiCrAlY and (Ni,Pt)Al across several substrates showed that Ti2Al(C1-xOx) consistently produced lower stresses, particularly near the thermally grown oxide (TGO)–BC interface where failure usually initiates. These results indicate that oxygen incorporation, unavoidable in practical situations, can be used to tune Ti2AlC for improved reliability, supporting its use as a next-generation BC.

Author: H.Kim†, H.Lee†, K.Lee, J.Choi, S.Jeong, J.Kim*Title: Enhanced aqueous stability of Sc4N3O2 over Sc4C3O2 MXene Cathodes: Aqueous Zn ion batteriesJournal: Applied Surface ScienceYear: 2026Impact factor: 6.9Abstract:Sc-based MXenes have emerged as promising candidates for next-generation aqueous Zn ion battery (AZIB) cathodes; however, their synthesizability, aqueous stability, and electrochemical suitability remain insufficiently explored. Here, we comparatively evaluate Sc4N3O2 and Sc4C3O2, using ab initio calculations and ab initio molecular dynamics simulations. The thermodynamic stability of the corresponding MAX precursors, Sc4AlN3 and Sc4AlC3, confirms the synthesizability, while Al binding energy calculations support the feasibility of MAX-to-MXene transformation. Binding energy analysis indicates that O termination is energetically preferred over F. Electronic structure analysis reveals excellent conductivity in both MXenes, with Sc4N3O2 demonstrating stronger Sc-N covalent bonding than Sc4C3O2. Both materials deliver high theoretical Zn-ion storage capacities of 844.62 and 879.15 mAh/g, respectively, exceeding those of conventional cathodes (e.g., β-MnO2: 375 mAh/g and V2O5: 224 mAh/g). The aqueous stability is then investigated in H2O and various Zn-based electrolytes, including ZnCl2, ZnSO4, Zn(TFSI), and Zn(CF3SO3). Analysis of Sc(MXene)-O(H2O) and Sc(MXene)-Zn(electrolyte) distance evolution reveals that Sc4N3O2 maintains structural integrity across all electrolyte conditions, whereas Sc4C3O2 undergoes structural degradation in Zn(CF3SO3) and ZnSO4 electrolytes. This behavior is consistent with the stronger Sc–N bonding identified in the electronic-structure analysis, which suppresses destabilizing metal-ion interactions at the interface.