Multilayer Stack Research Articles

Efficient and Scalable Radiative Cooling for Photovoltaics Using Solution‐Processable and Solar‐Transparent Mesoporous Nanoparticles

AbstractContinuous heat generation in perovskite solar cells (PSCs), caused by solar radiation, poses a significant challenge to their lifespan. Existing active cooling methods require extra energy input and might not be effective at high temperatures. Most reported passive radiative cooling materials either lack solar transparency or require complex fabrication processes. Here, mesoporous silica nanoparticles are designed, synthesized, and assembled into multilayered stacks with a graded refractive index (GRI) by spray coating them on top of PSCs made from methylammonium lead iodide (MAPbI3) over a large scale (15.6 × 15.6 cm2). This coating offers both high transparency in the visible wavelength and high emissivity in the mid‐infrared region, leading to an average temperature reduction of 6.65 ± 1.48 °C in GRI‐coated MAPbI3 PSCs under outdoor conditions compared to non‐coated references. After 50 d, the GRI‐coated PSCs maintain 80.9 ± 8.7% of their initial photoconversion efficiency, in contrast to 6.1 ± 5.9% for the noncoated ones. The calculated cooling power of the GRI‐coated PSCs is 28.9% higher than that of the reference cells.

Adhesion layers between piezoelectric and magnetostrictive layers in a MEMS magneto-sensor stack: Influence on the phase transformation of deposited Co/Fe multilayers to magnetostrictive CoxFe1−x phase

Magnetoelectric MEMS devices, such as magnetic field sensors, may be composed of a multilayer stack as a magnetostrictive layer, which is mechanically coupled to a piezoelectric film. Good adhesion and a stable rigid interface have to be maintained for such a sensor. Certain electric and magnetic properties, especially the magnetostriction, have to reach sufficiently high values, which can be achieved by selected phases or mixtures of phases. In this study, Co/Fe multilayers with varied bilayer periods are deposited onto AlN or Sc0.14Al0.86N coated Si substrates by DC magnetron sputtering with the optional insertion of a 5 nm thick adhesion layer of Cr or Zr to investigate its influence on the formation of the desired mixture of bcc and fcc Co0.7Fe0.3 phases, which are expected to yield a high magnetostrictive strain, after an RTA at 800 °C. A qualitative phase analysis is made by XRD in Bragg-Brentano geometry and shows that the bcc + fcc mixture can be achieved with a Cr interlayer. A sharp, void free, and undamaged interface for that case was observed in SEM images of cross sections prepared with FIB.

Application of Machine Learning Models for Malware Classification With Real and Synthetic Datasets

Stacking of multiple Machine Learning (ML) classifiers have gained popularity in addressing anomalous data classification along with Deep Learning (DL) algorithms. This study compares traditional ML classifiers, multi-layer stacking ML classifiers, and DL classifiers using an open-source malware dataset-containing equal numbers of benign and malware samples. The results on the realistic dataset indicate that the DL classifier, utilizing a Bidirectional Long Short-Term Memory (BiLSTM) model, outperformed the stacked classifiers with Logistic Regression (LR) and Support Vector Machine (SVM) as Meta learners by 36.78% and 39.69%, respectively, in terms of classification accuracy and performance. The research work was extended to study the impact of Generative Adversarial Network (GAN) based synthetic dataset of relatively smaller size on deep learning models. It was observed that the Deep Learning Multi-Layer Perceptron (DLMLP) Model had relatively superior performance as compared to complex deep learning models like Long Short-Term Memory LSTM and BiLSTM

Numerical simulation and experimental analysis of thermal conduction and stress in laser cladding repair of thin-walled parts

To minimize the deformation of thin-walled parts during the laser cladding process and enhance the quality of the repaired parts, the Finite Element Abaqus software was used to develop a thermal conduction and 3D stress model, the heat source used in the experiments was a double ellipsoid heat source model. This model simulates the thermal process and the deformation resulting from residual stresses in the laser cladding process on a titanium alloy substrate with a thickness of 2 mm. Through the simulation, the temperature field of the substrate at the end of each pass was obtained, and the cladding sequence with the smallest temperature gradient during the multi-pass laser melting process was determined. By combining simulation and practice, the multilayer stacking pattern was optimized to achieve deformation control. Analog simulation experiments indicate that the optimized single-layer multi-pass laser cladding method results in less heat accumulation and thermal stress compared to the unidirectional sequential scanning method. The flatness test results show that the specimens have less deformation with the optimized multilayer stacking method. In addition, the metallographic organisation of the two cladding specimens is analysed in this paper, and the results show that the optimised specimens exhibit excellent microstructures and properties.

A Mussel-Inspired and Recyclable Coating with Integrated Daytime Radiative Cooling and Triboelectric Energy Harvesting for Intelligent and Sustainable Buildings.

Carbon neutrality necessitates new technologies for renewable energy utilization, active regulation of heat exchange, and material recycling to promote green and intelligent building development. Currently, the integration of these functions and characteristics into a single coating material presents a significant challenge. Here, we demonstrate a novel triboelectric and radiative cooling coating with mussel-inspired architectures, fabricated using cellulose nanofibers and Mica-TiO2 as a functional mortar and brick, respectively. The abundant polar groups and specific surface area of cellulose nanofibers enable a high accumulation of induced electrostatic charges, allowing the coating to act as a tribolayer to generate triboelectric outputs. The regularly layered arrangement of Mica-TiO2 endows fire resistance to the coating, which exhibits self-extinguishing properties and maintains 45% of its original electrical output even after direct exposure to flame for 20 s. Additionally, the created multilayered stacking morphology, as well as intense group vibrations of Mica-TiO2, facilitates high reflectivity (Rsolar = 0.9) and long-wave infrared emissivity (ϵLWIR = 0.94), achieving a daytime subambient temperature drop of 5.3 °C. Notably, the coating can be recycled easily while maintaining its triboelectric, radiative cooling, and fire-resistant properties. This work provides an innovative strategy for unifying triboelectric and radiative cooling functions, as well as recyclability, into a single coating material, offering new insights for future sustainable and energy-efficient buildings.

An ultrasensitive flexible force sensor with nature-inspired minimalistic architecture to achieve a detection resolution and threshold of 1 mN for underwater applications

Highly sensitive flexible force sensors enable precise detection of underwater signals for monitoring biological activity, environmental conditions, and vehicle movement. Multilayer stack assembly and micro/nano structure array are often seen in most force/pressure sensors which are toughly hard to control the interlayer spacing and micro/nano structures alignment precisely, resulting in poor consistency and stability. Herein, we first reported a new force sensor with a nature-inspired minimalistic architecture, addressing such issues in an elegant and surprising approach by using a single-layer arched functional membrane with one microgroove. Inspired by the scorpions’ slit sensilla and mantis’ campaniform sensilla, a highly sensitive and waterproof flexible force sensor was fabricated. It is demonstrated that the force sensor has a sensitivity of 27.6 N−1, a high force resolution (1 mN), a fast response time of 70 ms, excellent stability over 5000 cycles and linearity (0.996), and a small force detection limit (≤ 1 mN), showing great potential in underwater environment sensing and motion monitoring of vehicles. This novel but minimalistic architecture provides a new direction in the development of sensors with advanced performance.

Influence of dislocations in multilayer graphene stacks: A phase field crystal study

Influence of dislocations in multilayer graphene stacks: A phase field crystal study

Flexible MXene/CuNWs/Tartaric Acid composite fabrics constructed by stacking assembly for Electromagnetic Interference Shielding

With the rapid development of modern communication technology, the exploration of flexible wearable shielding fabrics with exceptional electromagnetic interference (EMI) shielding performance has emerged as an utmost priority to safeguard both human beings and electronic devices from the detrimental effects of electromagnetic radiation. Herein, a scalable multilayer stacking assembly method is proposed to prepare uniform MXene/CuNWs/Tartaric Acid (TA) composites-coated fabrics. MXene, as a new type of material, can achieve higher electron and ion transfer rates. However, it is prone to oxidation in air, leading to poor stability. Benefiting from the synergistic effect of tartaric acid, the MXene/CuNWs/TA-coated fabrics exhibit certain oxidation stability and corrosion resistance, while retaining the inherent flexibility and breathability of natural polymer textiles. Furthermore, the multilayer stacking structure works perfectly with the MXene/CuNWs conductive network, enabling multiple reflections and absorptions of electromagnetic waves internally, thus effectively diminishing energy transmission. The modified fabrics exhibit a low sheet resistance of 3.25 ± 0.12 Ω/sq and a good EMI shielding performance of 41.2 dB at X-band. Therefore, MXene/CuNWs/TA fabrics with high shielding performance are expected to reach their potential in wearable electronic products.

Molten pool behaviors and printability of tungsten anti-scattering grids with extremely thin wall thickness fabricated via laser powder bed fusion

It is challenging for laser powder bed fusion (LPBF) technique to fabricate metal parts with a wall thickness below 100 μm. This work investigated the critical conditions for achieving extremely thin wall thickness in tungsten grids fabricated via LPBF. Specifically, the impact of low energy density on the printability of tungsten single tracks and grids via LPBF was comprehensively examined. A computational fluid dynamics approach was employed to develop a thermal fluid flow model for single tracks with multilayers in LPBF. The findings demonstrate that at low energy densities, single tracks exhibit four different morphologies, i.e., balling, discontinuity and winding, discontinuity but straightness, as well as continuity and straightness. The simulation model effectively elucidates the continuity of single tracks and provides insights into the governing mechanism of molten pool defects. Due to high thermal diffusion properties of tungsten, the continuity of its track relies on the connection of neighboring molten pools and is sensitive to scanning speed. The tungsten molten pools with low energy density can be categorized into shallow flows affected by surface morphology and deep flows influenced by internal voids of the powder bed. After multi-layer stacking, the track fluctuations and defects in single tracks accumulated into greater surface roughness and deteriorate thin-walled morphology. The critical conditions required for printing extremely thin walls were achieved, ensuring minimal merging of tracks between two layers by maintaining the energy density of 57J/mm3. Based on these findings, an ultra-thin-walled anti-scattering tungsten grid with a wall thickness of 86 μm and a wall roughness below 3.3 μm (Ra) was fabricated by LPBF. This work provides valuable theoretical insights and presents a viable methodology for determining the minimum energy density threshold and wall thickness essential for LPBF processing of thin-walled components.

An instrumentation guide to measuring thermal conductivity using frequency domain thermoreflectance (FDTR).

Frequency Domain Thermoreflectance (FDTR) is a versatile technique used to measure the thermal properties of thin films, multilayer stacks, and interfaces that govern the performance and thermal management in semiconductor microelectronics. Reliable thermal property measurements at these length scales (≈10nm to ≈10μm), where the physics of thermal transport and phonon scattering at interfaces both grow in complexity, are increasingly relevant as electronic components continue to shrink. While FDTR is a promising technique, FDTR instruments are generally home-built; they can be difficult to construct, align, and maintain, especially for the novice. Our goal here is to provide a practical resource beyond theory that increases the accessibility, replicability, and widespread adoption of FDTR instrumentation. We provide a detailed account of unpublished insights and institutional knowledge that are critical for obtaining accurate and repeatable measurements of thermal properties using FDTR. We discuss component selection and placement, alignment procedures, data collection parameters, common challenges, and our efforts to increase measurement automation. In FDTR, the unknown thermal properties are fit by minimizing the error between the phase lag at each frequency and the multilayer diffusive thermal model solution. For data fitting and uncertainty analysis, we compare common numerical integration methods, and we compare multiple approaches for fitting and uncertainty analysis, including Monte Carlo simulation, to demonstrate their reliability and relative speed. The instrument is validated with substrates of known thermal properties over a wide range of isotropic thermal conductivities, including Borofloat silica, quartz, sapphire, and silicon.

Photovoltaic effects in BiVO4/ZnTiO3 multilayer films with high fill factor

Bismuth-based semiconductor materials have garnered significant attention because of their appropriate optical bandgap and substantial photoelectric conversion efficiency. Enhancing the photocurrent and fill factor of photovoltaic films is essential for developing high-performance optoelectronic devices. In this study, high-performance BiVO4-ZnTiO3 multilayer films were fabricated using a straightforward sol-gel method, where the incorporation of ZnTiO3 films significantly improved the photovoltaic performance of BiVO4. Through structural design aimed at enhancing light utilization, the BiVO4-ZnTiO3 multilayer film achieved a photocurrent density of 1.9 mA/cm2 at 450 nm, along with a fill factor of 46.8 % in the composite multilayer structure. The improvement in film performance is attributed to the overall multilayer stacking effect. This study offers a novel approach for utilizing bismuth-based semiconductors in optoelectronics.

Selective IR wavelengths multichannel filter based on the one-dimensional topological photonic crystals comprising hyperbolic metamaterial

In this research article, we have theoretically introduced a one-dimensional topological photonic crystal (1D TPC) design to provide a better stability due to imperfections and fluctuations in geometry compared to the traditional PC structures. The considered structure is designed by the combination of two different PCs, i.e., PC1 and PC2. PC1 consists of two layers of silicon (Si) and magnesium fluoride (MgF2), while PC2 contains a multilayer stack of MgF2 and hyperbolic metamaterial (HMM). Interestingly, the HMM layer is introduced as a composite of a dielectric material of indium arsenide (InAs), and nanocomposite of Ag nanoparticles inside a hosting medium of Y2O3. The foundations of our theoretical framework are based on Effective Medium Theory (EMT), the Transfer Matrix Method (TMM), and the Maxwell-Garnett model. Our research primarily focuses on utilizing our design as a pass/stop band filter for near-infrared (NIR) applications. Notably, this proposed design exhibits significant stability in the face of imperfections and variations. Our numerical findings highlight the influence of several geometric parameters including the refractive index of hosting medium for Ag nanoparticles, thicknesses, and filling fraction on the characteristics of the resulting filter. Remarkably, the results also reveal the emergence of multiple resonance peaks that maintain high stability against geometric tolerances. We believe our work presents a finite photonic crystal (PC) whose wave localization properties are resilient to random geometric imperfections, making it suitable for NIR filtering applications.

Investigating the impact of shear and bulk viscosity on the damping of confined acoustic modes in phononic crystal sensors

Phononic crystal (PnC) sensors are recognized for their capability to control acoustic wave propagation through periodic structures, presenting considerable potential across various applications. Despite advancements, the effects of fluid viscosity on PnC performance remain intricate and inadequately understood. This study theoretically investigates the influence of shear (dynamic) and bulk viscosity on acoustic wave damping in defective one-dimensional phononic crystal (1D PnC) sensors designed for detecting liquid analytes. Acetic acid with varying viscosities is considered to fill a cavity layer intermediated by a multilayer stack of lead and epoxy. The effects of dynamic and bulk viscosity on the resonance characteristics of the defective mode were analyzed. Numerical results reveal that increased dynamic viscosity leads to substantial broadening and decreased intensity of resonance peaks, accompanied by a shift to higher frequencies due to enhanced elastic wave attenuation and damping. At low dynamic viscosity (η = 0.2 ηd), numerous resonance peaks with varying intensities are observed. However, at higher viscosities (η = 2.0 ηd to η = 10.0 ηd), only one prominent peak appears in the spectrum. The intensity of this resonant peak starts at 98% for η = 2 ηd and decreases to 58.8% as the dynamic viscosity increases to η = 10 ηd. Additionally, the combined effect of dynamic and bulk viscosity introduces further damping, causing a strong shift of the resonance peak to higher frequencies, along with an increase in the full width at half maximum (FWHM) and a decrease in the quality factor (QF). These findings emphasize the necessity of incorporating both shear and bulk viscosity in the design of PnC sensors to enhance their sensitivity and accuracy in practical applications. This theoretical framework provides critical insights for optimizing sensor performance and bridging gaps between theoretical predictions and experimental observations, especially in 1D PnCs, offering potential solutions to challenges in real-world PnC sensor applications.

Enhancement of high-frequency harmonics in resonators using multilayered structures with polarity-inverted layers

Periodically Poled Piezoelectric Film (P3F) stacks have recently been reported as a promising platform for next-generation radio-frequency acoustic filters that extend into cm- and mm-wave bands. By demonstrating the potential for developing high-performance acoustic devices with frequencies up to 20 GHz, P3F structures based on lithium niobate (LiNbO3) films have opened up new possibilities. In this study, the influence of key parameters such as the number of layers, crystal orientation, duty factor, and variation in thicknesses between the layers on the efficiency of the n-th harmonic excitation and spurious modes was examined. To enhance higher-order harmonics, which are suppressed in P3F structures, a novel multilayered stack with Aperiodically Polarized Piezoelectric Films (APPF) is proposed. Optimizing the ratio between layer thicknesses can enhance higher-order harmonics. An optimization principle is described and illustrated by examples of three-layered APPF structures optimized for the generation of antisymmetric Lamb wave harmonics A3-A17, with electromechanical coupling continuously decreasing with frequency. High-frequency modes excited in APPF structures fill the gaps in frequencies and electromechanical coupling coefficients between the modes generated in P3F stacks and can provide greater diversity of device performance.

(Keynote) Epitaxial Si/SiGe Multi-Stacks: From Stacked Nano-Sheet to Fork-Sheet and CFET Devices

After a short description of the evolution of metal-oxide-semiconductor (MOS) device architectures and the corresponding requirements on epitaxial growth processes, the manuscript describes the material properties of complicated Si/SiGe multi-layer stacks used for complementary field effect transistor (CFET) devices. They contain two different Ge concentrations and have been grown using conventional process gases. A relatively high growth temperature is used to obtain acceptable Si and SiGe growth rates. Still island growth has been suppressed for Ge concentrations up to 40%. Excellent structural and optical material properties of the Si/SiGe multi-layer stack will be reported, with up to 3 + 3 Si channels in the top and bottom part of the stack, respectively. The absence/presence of lattice defects has been verified by room temperature photoluminescence measurements. Photoluminescence measurements at low temperatures are used to study band-to-band luminescence from individual sub-layers and to illustrate the optical material quality of the CFET stack.

Achieving low-porosity AlSi10Mg cladding layers for the additive repair of aluminum alloy parts by directed energy deposition

Directed Energy Deposition (DED) has broad application prospects for repairing damaged aluminum alloy parts such as piston aero-engine casing. However, due to the low laser absorptivity and the complex thermal cycle process, it is challenging to obtain aluminum alloy cladding layers with high-quality morphology and low-porosity by DED method. In this work, a series of individual stages of DED process are studied during single-tracks overlapping and layers stacking. Correspondingly, the within layer scanning strategy, inter-layer stacking strategy, and process parameters are examined carefully. Using the proposed DED processing flow that combines substrate preheating with intermittent process, the deposited layers without balling and collapse are successfully achieved. Furtherly, the bi-directional scanning strategy for single-tracks overlapping within layer is proposed to compensate the thickness nonuniformity caused by heat accumulation. The inter defects identified as “lack of fusion” and “gas pores” are observed in the cladding layers with uniform surface. By analyzing the pore formation mechanism and considering the energy distribution and re-melting, the multi-layer offset stacking strategy is proposed to inhibit the porosity to 0.25 %. Combined with the optimized process parameters, the porosity is reduced up to 0.09 %, ensuring the density of the DED deposition coating. This work provides new pathway and direct guidance for fabricating high-quality AlSi10Mg cladding layers during the DED repairing of valuable aluminum alloy parts.

Applying deep learning-based ensemble model to [18F]-FDG-PET-radiomic features for differentiating benign from malignant parotid gland diseases.

To develop and identify machine learning (ML) models using pretreatment 2-deoxy-2-[18F]fluoro-D-glucose ([18F]-FDG)-positron emission tomography (PET)-based radiomic features to differentiate benign from malignant parotid gland diseases (PGDs). This retrospective study included 62 patients with 63 PGDs who underwent pretreatment [18F]-FDG-PET/computed tomography (CT). The lesions were assigned to the training (n = 44) and testing (n = 19) cohorts. In total, 49 [18F]-FDG-PET-based radiomic features were utilized to differentiate benign from malignant PGDs using five different conventional ML algorithmic models (random forest, neural network, k-nearest neighbors, logistic regression, and support vector machine) and the deep learning (DL)-based ensemble ML model. In the training cohort, each conventional ML model was constructed using the five most important features selected by the recursive feature elimination method with the tenfold cross-validation and synthetic minority oversampling technique. The DL-based ensemble ML model was constructed using the five most important features of the bagging and multilayer stacking methods. The area under the receiver operating characteristic curves (AUCs) and accuracies were used to compare predictive performances. In total, 24 benign and 39 malignant PGDs were identified. Metabolic tumor volume and four GLSZM features (GLSZM_ZSE, GLSZM_SZE, GLSZM_GLNU, and GLSZM_ZSNU) were the five most important radiomic features. All five features except GLSZM_SZE were significantly higher in malignant PGDs than in benign ones (each p < 0.05). The DL-based ensemble ML model had the best performing classifier in the training and testing cohorts (AUC = 1.000, accuracy = 1.000 vs AUC = 0.976, accuracy = 0.947). The DL-based ensemble ML model using [18F]-FDG-PET-based radiomic features can be useful for differentiating benign from malignant PGDs. The DL-based ensemble ML model using [18F]-FDG-PET-based radiomic features can overcome the previously reported limitation of [18F]-FDG-PET/CT scan for differentiating benign from malignant PGDs. The DL-based ensemble ML approach using [18F]-FDG-PET-based radiomic features can provide useful information for managing PGD.

A dual growth mode unique for organic crystals relies on mesoscopic liquid precursors

Organic solvents host the synthesis of high-value crystals used as pharmaceuticals and optical devices, among other applications. A knowledge gap persists on how replacing the hydrogen bonds and polar attraction that dominate aqueous environments with the weaker van der Waals forces affects the growth mechanism, including its defining feature, whether crystals grow classically or nonclassically. Here we demonstrate a rare dual growth mode of etioporphyrin I crystals, enabled by liquid precursors that associate with crystal surfaces to generate stacks of layers, which then grow laterally by incorporating solute molecules. Our findings reveal the precursors as mesoscopic solute-rich clusters, a unique phase favored by weak bonds such as those between organic solutes. The lateral spreading of the precursor-initiated stacks of layers crucially relies on abundant solute supply directly from the solution, bypassing diffusion along the crystal surface; the direct incorporation pathway may, again, be unique to organic solvents. Clusters that evolve to amorphous particles do not seamlessly integrate into crystal lattices. Crystals growing fast and mostly nonclassically at high supersaturations are not excessively strained. Our findings demonstrate that the weak interactions typical of organic systems promote nonclassical growth modes by supporting liquid precursors and enabling the spreading of multilayer stacks.

Improved performance of temperature sensors based on the one-dimensional topological photonic crystals comprising hyperbolic metamaterials

This paper seeks to progress the field of topological photonic crystals (TPC) as a promising tool in face of construction flaws. In particular, the structure can be used as a novel temperature sensor. In this regard, the considered TPC structure comprising two different PC designs named PC1 and PC2. PC1 is designed from a stack of multilayers containing Silicon (Si) and Silicon dioxide (SiO2), while layers of SiO2 and composite layer named hyperbolic metamaterial (HMM) are considered in designing PC2. The HMM layer is engineered using subwavelength layers of Si and Bismuth Germinate, or BGO (Bi4Ge3O12\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{Bi}}_{4}{\ ext{Ge}}_{3}{\ ext{O}}_{12}$$\\end{document}). The mainstay of our suggested temperature sensor is mainly based on the emergence of some resonant modes inside the transmittance spectrum that provide the stability in the presence of the geometrical changes. Meanwhile, our theoretical framework has been introduced in the vicinity of transfer matrix method (TMM), effective medium theory (EMT) and the thermo-optic characteristics of the considered materials. The numerical findings have extensively introduced the role of some topological parameters such as layers’ thicknesses, filling ratio through HMM layers and the periodicity of HMM on the stability or the topological features of the introduced sensor. Meanwhile, the numerical results reveal that the considered design provides some topological edge states (TESs) of a promising robustness and stability against certain disturbances or geometrical changes in the constituent materials. In addition, our sensing tool offers a relatively high sensitivity of 0.27 nm/°C.

A mechanical TiAl/TiAlN multinanolayer coating model based on microstructural analysis and nanoindentation

A finite element model reproducing the mechanical behaviour during nanoindentation tests on Ti0.67Al0.33/Ti0.54Al0.46N multilayer coatings was developed. Coatings with two different nanoperiods (10 and 50 nm) were deposited by radio-frequency magnetron sputtering from a single sintered titanium/aluminium target using the reactive gas pulsing process. X-ray diffraction and transmission electron microscopy confirmed the multilayer stacking of the coatings. The finite element models of coatings with these two stacking periods were built considering successive hypotheses: equal thicknesses for metal and nitride nanolayers stacked without transition layer, equal thicknesses stacking with a transition layer between each metal and nitride nanolayer and finally imbalanced thicknesses stacking with a transition layer. The elastic and plastic properties of the stacked nanolayers were determined on thick monolithic coatings of metal and nitride using indentation testing and the finite element model updating method respectively. The elastic-plastic properties of the interface were introduced in the multilayer model as a rule of mixtures of the metal and nitride properties using two hypotheses: parallel or serial. For 50 nm-period film, the interface has a negligible effect on the overall indentation response. On the other hand, for the 10 nm period, the imbalanced stacking model with precise knowledge of the transition layer thickness obtained by N K-edge electron energy loss spectroscopy is required to reproduce the experimental indentation curve. Compared to classical analytical models accounting for hardness, not only the hardnesses but also the indentation moduli appear to be well predicted and evaluated in this work.