Search Results (256)

Background/Objectives: Chronic myeloid leukemia (CML) is primarily associated with the BCR:ABL1 fusion protein. Although tyrosine kinase inhibitors (TKIs) have markedly enhanced treatment outcomes, the development of agents with improved therapeutic characteristics remains necessary. The present work focused on the synthesis of a new series of thiazolone derivatives (F1-11) and the assessment of their anti-CML activity through inhibition of ABL tyrosine kinase (TK). Methods: The designed compounds were prepared through a multistep synthetic pathway involving the formation of a new chalcone intermediate (A), synthesis of a new pyrazoline carbothioamide intermediate (B), and cyclization with different aldehydes to produce the target new thiazolone derivatives (F1-11). Cytotoxic effects were investigated against K562 CML cells using the MTT assay. The lead compound was additionally evaluated in HL-60 AML cells and normal PBMCs. Apoptotic induction was analyzed using Annexin V/ethidium homodimer staining, whereas ABL TK inhibitory activity was measured through the ADP-Glo assay. Molecular docking studies were conducted to explore ligand interactions within the ATP-binding domain of ABL TK. Results: Among the synthesized molecules, F-4 demonstrated the strongest activity against K562 cells with an IC₅₀ value of 6.85 µM, close to that observed for imatinib (IC₅₀ = 5.20 µM). The compound showed reduced cytotoxicity toward HL-60 cells (IC₅₀ = 33.44 µM) and exhibited favorable selectivity toward PBMCs (SI = 13). Apoptosis studies revealed 51% early apoptotic cells and 43% late apoptotic cells following treatment. In the kinase assay, F-4 inhibited ABL TK activity by 39% at 10 µM and by 70% at 100 µM. Docking simulations suggested interactions with residues His361 and Asp381 in addition to nearby hydrophobic amino acids, although the interaction network was less extensive than that of imatinib. Conclusions: The findings identify F-4 as a promising new thiazolone-derived scaffold with selective anti-CML activity and notable ABL TK inhibitory potential. Additional structural optimization may further enhance its binding characteristics and therapeutic efficacy. Full article

SiO₂ aerogels are promising candidates for energy-efficient glazing because of their low thermal conductivity and optical transparency; however, conventional formulations often fail to reconcile optical, thermal, and mechanical performance. This work aimed to resolve this bottleneck via controllable sol–gel synthesis and ambient pressure drying. Using methyltrimethoxysilane (MTMS) as the single silicon source, this study systematically explored the effects of alkaline catalyst type, water-to-MTMS ratio, and surfactant selection, and further developed an MTMS–dimethyl dimethoxy silicane (DMDMS) composite silicon source. Tetramethylammonium hydroxide (TMAOH) catalysis, a water-to-MTMS molar ratio of 7:1, and Pluronic F-127 (F127) surfactant yielded a uniform, hydrophobic aerogel with 93.50% porosity and 89.74% transmittance at 800 nm. The optimized composite system (MTMS:DMDMS = 9:1, 6 mL water, 2.0 g F127) enhanced compressive strength by 22.4% relative to pure MTMS aerogel, with 70.15% visible transmittance and thermal conductivity of 0.027 W/(m·K). These results demonstrate that multi-parameter formulation control can achieve a practical balance among mechanical robustness, optical transparency, and thermal insulation. This study provides a theoretical and process foundation for the engineering application of high-performance transparent thermal insulation materials. Full article

This work presents the design of a $\beta$-Ga₂O₃ MOSFET incorporating a P-type Ga₂O₃ buffer layer on a high-thermal-conductivity AlN/SiC composite substrate. The electrical characteristics of the device were simulated using Sentaurus TCAD. Results demonstrate that the integration of the composite substrate effectively mitigates self-heating effects, reducing the peak temperature ($T_{\mathit{max}}$) from 776.5 K to 570.9 K at 300 K, while simultaneously increasing the threshold voltage ($V_{\mathit{th}}$) from −0.35 V to 1.52 V. Through systematic optimization of the P-Ga₂O₃ buffer layer thickness and doping concentration, the device achieves a breakdown voltage ($V_{\mathit{br}}$) of 4781 V, a power figure of merit (PFOM) of 2.18 GW/cm², an $I_{DS}$, on/off ratio of 9.20 × 10⁹, and cut-off/maximum oscillation frequencies ($f_{\mathit{t}}$/$f_{\mathit{max}}$) of 1.29 GHz and 1.40 GHz, respectively. These findings provide a theoretical foundation for developing $\beta$-Ga₂O₃-based power devices with high breakdown voltage, improved thermal conductivity, and low specific on-resistance ($R_{\mathit{on},\mathit{sp}}$). Full article

The Lovozero and Khibiny alkaline massifs (Kola Peninsula, Russian Arctic) are the prominent sources of REE minerals, with the Lovozero loparite deposit being the only currently active REE mine in Russia. A new ashcroftine-related mineral phase KA with the idealized chemical formula K₆(Na₄Ca)(Y₈Ca₃Mn)[Si₂₈O₆₈(OH)₂](CO₃)₈F₂·9H₂O was found in the Khibiny alkaline massif. Its empirical formula determined by electron microprobe analysis is Na_4.14K_6.11Ca_3.89Mn_0.59Y_6.10Ce_0.08 Gd_0.32Tb_0.15Dy_0.78Ho_0.19Er_0.35Tm_0.15Yb_0.12Lu_0.06Si₂₈C₈O_93.02F_2.08·9H₂O. The crystal structure was determined and refined by means of single-crystal X-ray diffraction analysis. The KA phase is tetragonal, I4/mmm, a = 24.1661(3), c = 17.5914(4) Å, V = 10,273.4(3) ų. The crystal structure contains two Y sites. The Y1 site is [8]-coordinated and hosts more heavy REEs, whereas the Y2 site is predominantly [7]-coordinated and accumulates lighter REEs and Mn. The crystal structure is based upon the [Si₂₈X₇₀] nanotubes (X = O,OH) elongated along the c-axis and composed of corner-sharing SiX₄ tetrahedra. The external diameter of the tubules is equal to ~19.54 Å, i.e., slightly less than 2 nm. The silicate nanotubes are running parallel to the c-axis and centered along the (00z) and (½½z) directions. The tubules are linked by walls of YO_n polyhedra that also involve triangular CO₃ groups. The K⁺, Na⁺, and Ca²⁺ cations, as well as H₂O molecules, are located either inside or outside the tubules. The crystal-chemical formula of the KA phase can be written as {K_6.14Na_4.30Ca_0.81}[Y_5.88Ca_3.12Dy_0.88Mn²⁺_0.60Gd_0.32 Ho_0.24Er_0.24Tb_0.16Tm_0.16Er_0.12Yb_0.12Ce_0.08Lu_0.08](Mn³⁺_0.09) [Si₂₈O_68.36(OH)_1.65](CO₃)₈F₂·8.97H₂O, which agrees well with the idealized formula. According to the information-based complexity analysis, the KA phase has a very complex structure and belongs to less than 3.5% of the very complex minerals known today. The presence of silicate tubules is the key reason for the exceptional structural complexity of the phase. It is impossible to establish exact relations between the KA phase and ashcroftine-(Y) on the basis of the currently available data, since the last chemical analysis of the latter mineral was done in 1924. Therefore, the mineralogical identity of ashcroftine-(Y) is currently an unresolved problem. The silicate tubule in the KA phase is topologically related to the Linde zeolite A (the LTA zeolite framework) and can be produced from the latter by a series of topological operations. The KA phase forms a homological row with caysichite-(Y) and miyawakiite-(Y), along which the Si content is increasing, and silicate chains in caysichite-(Y) transform into silicate tubules in miyawakiite-(Y) and into silicate nanotubules in the KA phase. Indeed, the M:Si:C ratio (where M = Y, REEs, Ca, Mn, Fe) changes from 1:1:0.75 for caysichite-(Y) through 0.75:1:0.5 for miyawakiite-(Y) to 0.43:1:0.29 for ashcroftine-(Y) (and KA). The increasing role of silica along the row results in the formation of zeolite-derived porous one-dimensional units. The KA phase possesses two important crystal chemical properties that distinguish it from other minerals known to date: it hosts a variety of REEs and is based upon nanoscale zeolite-like silicate units. The KA phase, ashcroftine-(Y), caysichite-(Y), and miyawakiite-(Y) have never been prepared under laboratory conditions. The mineralogical occurrence of the KA phase in the Khibiny massif points out to its secondary origin, i.e., its formation under relatively soft, low-temperature hydrothermal conditions. Thus, the discovery of the KA phase in nature may provide important hints toward its synthesis in the laboratory by means of a soft-chemistry approach. Full article

The development of geopolymers as sustainable alternative binders has been accelerated by the environmental requirement to reduce the carbon footprint of cement. However, predicting their key properties, such as compressive strength, from their complex chemical composition remains a significant challenge. Although mixture ratios prepared on a macro-scale are widely used for quality control purposes, they do not account for the chemical structure, despite this having a direct impact on the materials’ structural properties. Predicting fundamental properties such as compressive strength from complex chemical compositions remains a significant challenge due to the nonlinear relationships between the elemental components. This research paper introduces a tailored hybrid machine learning framework that combines K-means clustering with classification algorithms. The method uses energy-dispersive X-ray spectroscopy (EDS) data to classify geopolymer samples into their specific mixture numbers, which allows scientists to predict material properties through compositional analysis. A new dataset featuring the elemental compositions of Si, Al, Na, Ca, O, and C, as well as the critical ratios of Si/Al and Ca/Si, was analyzed. The initial step involved clustering the data to discover natural compositional clusters, which served as the basis for training and testing five different classifiers, which included Random Forest (RF), Artificial Neural Networks (ANN), LightGBM, Naive Bayes (NB), and Linear Discriminant Analysis (LDA). The consequences proved that the hybrid method worked with outstanding efficiency. RF achieved the highest performance results through its 98% accuracy, 96% recall, 94% precision, and 95% F1-score results when it classified samples according to their clustered groups. SHAP (SHapley Additive exPlanations) and permutation feature importance analyses both showed that Si/Al proportion functioned as the most crucial predictive variable, while oxygen (O) content and silicon (Si) content followed in importance. The K-means cluster labels produced high accuracy results because they demonstrated that compositional data had strong natural groups, which matched the target property. The system delivers an efficient method which enables fast and dependable geopolymer property forecasts through direct analysis of chemical composition with chemical composition analysis, thus delivering essential information to enhance mix design processes and boost sustainable building material production. Full article

The selective removal of HCl from industrial HCl/SiF₄ mixtures was investigated using a series of alcohol-based and deep eutectic solvents (DESs). Among them, glycerol (GL) exhibited superior selectivity for HCl despite a moderate total capacity. Absorption at 60 °C ensured stable operation with minimal foaming. Desorption analysis revealed that both HCl and SiF₄ underwent partial irreversible absorption under N₂ stripping, while staged vacuum desorption enabled efficient and selective recovery—SiF₄ was fully removed at 70 °C and 6 kPa, followed by nearly complete HCl desorption at 90 °C. Cyclic tests confirmed excellent solvent stability and rapid regeneration, with complete desorption achieved within 10–15 min. A conceptual process was proposed based on these findings, demonstrating a practical and energy-efficient route for selective HCl recovery from acid–gas mixtures. Full article

Background/Objectives: Psychological stress triggers excessive melanin deposition via neuroendocrine pathways, yet targeted interventions for stress-induced hyperpigmentation remain limited. Salidroside (SAL) exhibits established depigmenting effects in UV-induced models and possesses neuroprotective properties. This study investigated SAL’s efficacy in psychological stress-induced hyperpigmentation and elucidated its underlying mechanisms. Methods: B16F10 melanocytes, C57BL/6J mice, zebrafish, and human foreskin organ cultures were subjected to stress factor (Substance P/cortisol) or α-MSH/IBMX stimulation to model psychological stress-induced and canonical cAMP-driven hyperpigmentation, respectively. Melanin content, tyrosinase activity, melanosome maturation (transmission electron microscopy/HMB45 staining), and melanogenic protein/mRNA expression were assessed. Drug Affinity Responsive Target Stability (DARTS) assays, molecular docking, and SEC23A siRNA knockdown were employed to identify and validate SAL’s molecular target and downstream signaling pathways. Results: SAL dose-dependently reduced melanin content, tyrosinase activity, and TYR/TRP-1/DCT expression in SP/Cort-stimulated melanocytes, exhibiting greater potency (200 μM) than in IBMX-induced models (400 μM). SAL reversed SP/Cort-induced hyperpigmentation in human skin explants, zebrafish, and C57BL/6J mice, and normalized melanosome number/maturation. DARTS and molecular docking identified SEC23A as a direct SAL-binding target. SP/Cort specifically upregulated SEC23A, which SAL suppressed. SAL concurrently activated the SEC23A-p-ERK-MITF axis and inhibited the NK1R-p38-MITF axis in the stress model. SEC23A knockdown potentiated SAL’s anti-melanogenic effects specifically in SP/Cort-stimulated cells. Conversely, in IBMX-induced models, SEC23A remained unchanged, and SAL acted via PKA/CREB, PI3K/AKT, and Wnt/β-catenin pathways. Conclusions: SEC23A is a novel core target in psychological stress-induced hyperpigmentation. SAL selectively binds SEC23A to inhibit stress-induced melanogenesis via dual ERK and p38 MAPK signaling axes, demonstrating etiological specificity distinct from canonical cAMP pathway inhibition. Full article

Iron oxide–copper–gold (IOCG) deposits are widespread throughout the Carajás Province, Brazil, reflecting multiple Precambrian hydrothermal events. The Aquiri region is a relatively unexplored geological frontier in the northwestern Carajás Province. The AQW2 IOCG deposit is hosted by a Neoarchean mafic intrusive suite within metavolcano–sedimentary rocks. The pre-mineralization (Na and Na-K) and mineralization (Fe-Ca and Fe-P) hydrothermal stages appear as replacement fronts and as cement within ductile-deformed breccias. Late-mineralization (Fe-K, chlorite, and calcic-rich) assemblages occur in multidirectional veins controlled by brittle structures. Early- and main-mineralization apatite (Ap I-III) is enriched in F, Mn, and Sr, depleted in Y, shows unusually high Fe and Si (Ap III), and exhibits a pronounced positive Eu anomaly (Ap II). These characteristics indicate an alkaline fluid composition, substantial fluid–rock interaction, and episodic CO₂ degassing with the release of overpressured fluids, resulting in multiple brecciation events. A rapid decrease in temperature due to boiling is interpreted as a principal mechanism for copper precipitation. Late-mineralization apatite (Ap V–VI) is characterized by relatively higher Cl, Y, and LREE contents, lower Sr and Mn, and negative Eu-anomaly ratios, suggesting control by shallower paleostructures and more oxidizing conditions associated with the influx of basinal brines. These results highlight the evolution of the AQW2 deposit within a broader IOCG system and provide new insights into the metallogenic processes responsible for copper resources essential to the clean energy transition. Full article

The continuous increase in power density of electronic devices imposes stringent requirements on the design of lightweight, high-efficiency heat sinks. To overcome the limitations of conventional single-gradient or monomaterial heat sinks—namely, their suboptimal heat-transfer efficiency and poor structural adaptability—this study proposes a dual-gradient, triply periodic minimal surface (TPMS)-based multimaterial heat sink architecture fabricated from CuCrZr and AlSi₇Mg. Thermal performance was quantified experimentally using infrared thermography, while the underlying flow-field mechanisms were investigated numerically via computational fluid dynamics (CFD) simulations employing the standard k–ε turbulence model. With the TPMS material volume ratio fixed at 3:3 (CuCrZr:AlSi₇Mg), the Z-axis gradient configuration P-Z4-5 delivered the best overall thermal performance, achieving a heat-transfer coefficient (HTC) of 1557.63 W·m⁻²·K⁻¹ and a thermal resistance as low as 1.83 K·W⁻¹ at an inlet velocity of 5 m·s⁻¹. In contrast, the Y-axis gradient configuration P-Y3-6 yielded the most uniform temperature distribution, exhibiting a maximum surface temperature difference of only 21.5 °C under the same inlet condition. Velocity and turbulence distribution analyses reveal that the dual-gradient design enhances both the narrow-tube effect and flow-induced disturbances; furthermore, increasing the inlet velocity from 5 m·s⁻¹ to 21.65 m·s⁻¹ significantly intensifies vorticity-driven fluid mixing. Among all configurations evaluated, P-Z4-5 exhibited the highest j/f factor (i.e., the ratio of Colburn j-factor to Fanning friction factor), followed by P-Z3.5-5.5 and P-Z3-6. These findings establish a promising new pathway for the development of high-performance, lightweight heat sinks tailored for next-generation high-power electronics. Full article

In the big-data-driven artificial intelligence era, similarity search, as a core operation in machine learning and data mining, demands high speed, energy efficiency, and scenario adaptability. Conventional electronic content-addressable memory (ECAMs) suffer from inherent RC delay bottlenecks, whereas existing optical content-addressable memory (OCAMs) are restricted by fixed bit-widths and limited distance metrics. In this work, we propose a variable bit-width all-optical CAM leveraging multi-segment modulators and phase-change material (PCM) Sb₂Se₃. The multi-segment memory unit (MSMU) therein compresses N-bit binary data into a single analog photonic unit, supporting direct data writing/loading without digital-to-analog converters (DACs) and flexible trade-offs between precision, storage capacity, noise immunity, and energy while enabling Hamming and nonlinear distance metrics. A six-element three-bit OCAM prototype was fabricated on a silicon nitride silicon-on-insulator (SiN-SOI) platform. Despite the absence of integrated high-speed phase shifters, the device still achieves reliable optical data storage and retrieval. K-nearest neighbor (kNN) simulations based on experimentally derived statistical data—validated on the iris, wine, and breast cancer datasets—show that the three-bit operating mode achieves classification accuracy comparable to Manhattan/Euclidean distances at high signal-to-noise ratios (SNRs), while the one-bit mode exhibits strong noise robustness. Energy consumption is 364 fJ/bit (3-bit) and 890 fJ/bit (1-bit). This work provides a high-speed, energy-efficient, and reconfigurable all-optical similarity search solution with experimentally verified device performance and dataset-validated applicability, showing great potential for widespread deployment in data-intensive machine learning and data-mining applications. Full article

The cement industry is central to sustainable manufacturing due to its high energy demand and associated CO₂ emissions. In cement production, a substantial share of electrical energy is consumed in the clinker grinding circuit, where Blaine fineness (specific surface area, cm²/g), a key quality output, affects both cement performance and specific energy consumption. However, laboratory Blaine measurements are typically available with a 30–60 min delay, which limits timely process interventions and may promote conservative operating practices (e.g., precautionary over-grinding) to secure quality. This study develops machine-learning models to predict the finished-product Blaine fineness (Blaine-F) from routinely recorded industrial quality-control inputs, including XRF-based oxide composition, derived chemical moduli (lime saturation factor, LSF; silica modulus, SM; alumina modulus, AM), laser-diffraction particle-size distribution descriptors (Q10/Q50/Q90 corresponding to D10/D50/D90 percentile diameters; and R3 residual fractions at selected cut sizes), and intermediate in-process fineness (Blaine-P). The models were trained on over 200 finished-product samples obtained from the quality-control laboratory information management system (LIMS) of Seza Cement Factory (SYCS Group, Turkey). Ridge regression, Random Forest, XGBoost, LightGBM, and CatBoost were tuned using RandomizedSearchCV with five-fold cross-validation and evaluated on a held-out test set using MAE, RMSE, and R². The results show that the linear baseline provides limited explanatory power (Ridge: R² ≈ 0.50), consistent with the strongly non-linear behavior of the grinding–separation system, whereas tree-based ensemble methods achieve higher predictive accuracy. XGBoost yields the best overall performance (R² = 0.754; RMSE = 76.9 cm²/g), while Random Forest attains R² = 0.744 with the lowest MAE (61.7 cm²/g). Explainability analyses indicate that Blaine-F is primarily influenced by the fine-tail PSD descriptor Q10 (D10 particle size) and the intermediate fineness Blaine-P, whereas chemistry-related variables (e.g., LSF and SiO₂, and particularly SM) provide secondary yet meaningful contributions. These findings support the use of the proposed model as a virtual sensor to reduce decision latency associated with delayed laboratory Blaine measurements and to enable tighter fineness targeting. Potential energy and CO₂ implications should be quantified using site-specific, plant-calibrated relationships between kWh/t and Blaine fineness, rather than inferred as measured outcomes within the present study. Full article

This work presents a comprehensive quantum transport modeling and simulation framework to evaluate parasitic effects and radio frequency (RF) performance in stacked silicon (Si) nanosheet (NS) lateral gate-all-around (LGAA) nFETs targeting the sub-2 nm technology node. Leveraging the non-equilibrium Green’s function (NEGF) method, the proposed framework integrates detailed modeling of parasitic resistances (R_para) and capacitances (C_para) to enable a holistic analysis of both intrinsic and extrinsic figures-of-merit, including transconductance (g_m), output conductance (g_d), cutoff frequency (f_T), and maximum oscillation frequency (f_max). The effects of nanosheet geometry, crystal orientations, and dual-k spacers on high-frequency performance are systematically investigated. The analysis reveals key design trade-offs, with optimized device configurations yielding f_T exceeding 400 GHz and f_max approaching 1.2 THz. These findings highlight the potential of stacked NS LGAA-nFETs for future millimeter-wave and terahertz applications, providing critical insights into parasitics management and quantum-transport-aware design strategies at advanced CMOS nodes. Full article

To address the challenges of ambient light interference and slow overload recovery in transimpedance amplifiers (TIAs) for automotive Light Detection and Ranging (LiDAR) systems, this paper proposes a high-performance TIA with integrated ambient light cancellation and fast recovery capabilities. The core design includes an adaptive ambient light cancellation (ALC) loop that eliminates background currents up to 3 mA without relying on AC coupling capacitors, achieving a low-frequency cutoff frequency of 321 kHz to ensure the signal-to-noise ratio (SNR) of weak target signals. A multi-stage clamping and current transfer mechanism is employed to realize rapid overload recovery: under 100 mA heavy overload conditions, the recovery time is controlled around 8.7 ns, and the pulse broadening is limited to 2.7 ns, avoiding measurement blind zones. Implemented in a 0.18-μm SiGe BiCMOS process, the proposed TIA occupies a compact area of 0.15 mm², with a transimpedance gain of 80 dBΩ (10 kΩ) and a −3 dB bandwidth of 421 MHz. The input-referred noise current spectral density is 4.7 $\mathrm{pA}/\sqrt{\mathrm{Hz}}$, and the integrated equivalent input noise current from 1 Hz to 250 MHz is 73.6 nA_rms. Operating over a temperature range of −40 ℃ to 125 ℃, the TIA meets the rigorous requirements of automotive-grade applications. Performance comparisons with commercial products and state-of-the-art designs demonstrate its competitive ambient light rejection and fast recovery capabilities, validating its potential for use in direct time-of-flight (dToF) LiDAR systems for autonomous driving. Full article

Perovskite quantum dots (PQDs) based on CsPbX₃ (X = Cl, Br, I) have attracted extensive attention due to their outstanding optoelectronic properties; however, their practical applications are hindered by poor environmental stability. In this work, a sequential surface-modification strategy is developed to address these limitations. First, CsPbBr₃ PQDs are passivated with (3-aminopropyl) triethoxysilane (APTES), which reduces surface defects and enhances the photoluminescence quantum yield (PLQY) from 38.5% to 74.4%. Subsequently, a dense silica shell is constructed via in situ hydrolysis of tetramethyl orthosilicate (TMOS), further improving the PLQY to 95.6% and significantly boosting environmental stability. Structural and optical characterizations confirm effective defect passivation and suppress non-radiative recombination, with carrier lifetimes extended from 2.5 ns to 36.9 ns. Remarkably, the silica-coated PQDs retain over 50% of their initial emission intensity after 100 min of water immersion, far exceeding the stability of uncoated counterparts. Furthermore, when integrated with a commercial K₂SiF₆: Mn⁴⁺ red phosphor and a blue light-emitting diode (LED) chip, the resulting white LED (WLED) exhibits a wide color gamut covering 104% of the National Television System Committee (NTSC) standard and Commission Internationale de l’Éclairage (CIE) coordinates of (0.323, 0.331), closely matching standard white light. Importantly, only the silica-coated PQDs maintain a stable electrically driven device emission spectrum after water exposure. Full article

This paper investigates the feasibility of CaZr₄(PO₄)₆ as a novel thermal barrier coating for SiO_2f/SiO₂, serving as a radome at 1200 °C. Initially, CaZr₄(PO₄)₆ powder undergoes TG-DSC testing across a temperature range from room temperature to 1200 °C, demonstrating excellent phase stability within this range. Subsequently, the coating’s properties and the thermal cycling performance are examined. The results indicate that the thermal conductivity of CaZr₄(PO₄)₆ falls within the range of 1.05 to 1.02 W·m⁻¹·K⁻¹ (RT ~ 1200 °C), with thermal expansion coefficients of the coating ranging from 2.07 to 5.55 × 10⁻⁶ K⁻¹. Moreover, the thermal cycling lifetime of the CaZr₄(PO₄)₆ coating is evaluated by performing 100 cycles (50 h) at 1200 °C. Mechanical properties are assessed through Vickers and Knoop hardness tests, revealing a fracture toughness of 1.4 Mpa·m^1/2. The primary cause of coating failure and peeling is the excessive internal stress between the coating and the expansion of transverse cracks. Fracture toughness serves as a key performance indicator reflecting the material’s resistance to unstable crack expansion, so the failure of the coating is attributed to the limited fracture toughness and the thermal mismatch stress between the coating and the substrate. Based on the aforementioned research findings, CaZr₄(PO₄)₆ might be the potential coating for SiO_2f/SiO₂ systems. Full article