Search Results (198)

Group III-nitride semiconductors (GaN, AlN, InN) serve as foundational materials for modern optoelectronics, high-frequency microelectronics, and next-generation energy harvesting devices. However, traditional high-temperature epitaxy (>700 °C) introduces severe thermal stress, high dislocation densities, and fundamental incompatibility with flexible substrates or CMOS back-end-of-line (BEOL) processes. Plasma-enhanced atomic layer deposition (PEALD) provides a disruptive, ultra-low thermal budget (<300 °C) pathway for atomic-scale precision growth and conformal coating. This review systematically summarizes recent frontiers in PEALD-synthesized Group III-nitrides and 2D/3D polar heterostructures. First, we dissect the microscopic nucleation kinetics, surface bond reconstruction, and impurity suppression mechanisms across diverse substrates, including Si, sapphire, quartz, metals, and flexible polymers. Next, we highlight 2D template-assisted van der Waals epitaxy on graphene and MoS2, and elucidate polarization-driven dipole interactions and band alignment engineering at 2D/3D polar interfaces (e.g., α-In₂Se₃, Janus MoSSe). Furthermore, we comprehensively discuss innovative applications in advanced photovoltaics (as electron transport and passivation layers in perovskite and quantum dot-sensitized solar cells), silicon-based microcavity lasers, high-electron-mobility transistors (HEMTs), and flexible multimodal sensors. Finally, key technological challenges—including the low-thermal-budget paradox, wafer-scale uniformity, and deposition throughput—are addressed alongside future perspectives in area-selective ALD and neuromorphic computing, presenting a cohesive blueprint from underlying physics to macroscopic system integration. Full article

Conventional photodetectors and image sensors deliver high-fidelity digital outputs but face a growing data-movement bottleneck: the energy and latency cost of transferring raw pixel streams to off-chip memory and processors increasingly dominates over both sensing and computation in modern machine-vision pipelines. An emerging response is the neuromorphic photodetector, a class of optoelectronic device that converts incident light into an electrical signal while simultaneously storing, modulating, and pre-processing that signal in a manner inspired by biological synapses and retinas. Over the past decade, demonstrations have spanned at least eight material platforms—organic semiconductors, organic–carbon-nanotube hybrids, perovskite and perovskite hybrids, metal oxides (including ultra-wide-bandgap and printable variants), wide-bandgap III-nitrides and 4H-SiC, two-dimensional materials, photo-memristors, and silicon CMOS in-sensor compute architectures—and have been realised through four distinct architectural families: phototransistor synapses, photo-memristors, heterojunction in-sensor compute, and linear photovoltaic neural networks. Here, we provide a quantitative cross-platform benchmark across forty in-scope articles, identify persistent photoconductivity as a near-universal device-physical substrate underlying synaptic functionality, characterise the responsivity–speed–energy trade-off structure observed across platforms, and present a critical assessment of energy-reporting practice in the field. We further identify three best-practice exemplars from three independent material platforms that converge on operating biases of 0.01–0.1 V and energies of 0.07–0.8 fJ per event, and we propose a unified reporting framework to enable meaningful cross-platform benchmarking of next-generation neuromorphic photodetectors. Full article

Bandstructure methods occupy a central place in the physics of nanostructures, and the multiband $\mathit{k}·\mathit{p}$ theory of Luttinger, Kohn, and Kane has served as one of the most widely used computational frameworks for modelling electronic states and energies in low-dimensional semiconductor systems for several decades. Despite its broad success, the theory harbours a fundamental mathematical difficulty that has been largely overlooked: the multiband Luttinger–Kohn Hamiltonians are non-elliptic partial differential operators for the overwhelming majority of common III–V and III-nitride crystalline materials, a fact that violates the axiomatic requirements of quantum mechanics and is the root cause of the long-standing problem of spurious solutions. In this paper, we derive ellipticity conditions rigorously for the $6\times 6$, $8\times 8$, and $14\times 14$ zinc-blende Hamiltonians, demonstrating that non-ellipticity affects a substantially larger class of materials than previously reported. We develop and justify a systematic parameter rescaling procedure for the $8\times 8$ Kane Hamiltonian and obtain admissible parameter sets for GaAs, AlAs, InAs, GaP, AlP, InP, GaSb, AlSb, InSb, GaN, AlN, and InN. The inversion-asymmetry parameter B is shown to play an essential and previously unrecognized role in maintaining ellipticity, and it is used to optimize the bandstructure fit of the rescaled parameter sets. Analysis of several known $14\times 14$ models reveals structural sources of non-ellipticity, pointing to the need for a revision of perturbative assumptions regarding out-of-basis band contributions. The consistent parametrization framework developed here provides the rigorous mathematical foundation required by inverse design methodologies, AI-enhanced electronic structure calculations, and data-driven multifidelity approaches in nanoscience and nanotechnology. Full article

With the advent of 6G mobile communication, the demand for ultra-high bandwidth wireless communication has increased rapidly, drawing significant attention to visible light communication (VLC) as a promising emerging technology. GaN-based laser diodes (LDs) are regarded as high-speed light sources for VLC owing to their high modulation bandwidth and high optical power density. Apart from the active region design, the LD’s structure also plays a crucial role in determining their dynamic properties, which have yet to be thoroughly studied in III-nitride LDs. In this work, we systematically investigate InGaN/GaN laser diodes with three ridge waveguide configurations: a conventional single-ridge structure, a dual-ridge large-mesa structure, and a dual-ridge small-mesa structure. The threshold current, small-signal modulation bandwidth of devices with different structures are comparatively analyzed. Experimental results reveal that the double-ridge small mesa laser diode achieves a modulation bandwidth of −3 dB at 6.02 GHz. These results provide valuable insights into the structural optimization of GaN-based high-speed laser diodes and offer practical guidance for the development of high-performance, energy-efficient VLC transmitters. Full article

To achieve an atomically clean surface of single-crystal aluminum nitride (AlN) substrates, this study systematically evaluated the effects of each step in ex situ wet chemical cleaning (solvent, piranha solution, HF, HCl) and in situ hydrogen annealing. X-ray photoelectron spectroscopy (XPS) and atomic force microscopy (AFM) analyses revealed that while the combination of solvent and piranha solution exposed step morphology, its effectiveness in removing organic contaminants was limited. HF cleaning efficiently removed the oxide layer but introduced fluorine residues, whereas HCl cleaning left no chlorine residues but exhibited lower efficiency in oxide removal. In situ hydrogen annealing significantly reduced carbon and oxygen contamination, albeit accompanied by a transformation of the surface morphology from step to island mode. By modulating the low V/III ratio during low-temperature metal–organic chemical vapor deposition (MOCVD) growth, a controlled transition from 3D island growth to 2D step-flow growth was achieved. This research provides a basis for optimizing AlN substrate surface treatment, offering important insights for advancing nitride-based optoelectronic and power devices. Full article

High-temperature operation of AlGaN/GaN Heterojunction Field Effect Transistor embedded diaphragm-based MEMS pressure sensors have been investigated, which utilized their wide bandgap and piezo resistivity to perform stably at elevated temperatures. The performance of the pressure sensor was observed over a change in applied pressure of 35 kPa, which resulted in an experimentally measured change in drain–source resistance (ΔR_DS/R_DS(0)) of 0.32% at room temperature and 0.65% at 250 °C, respectively. Additionally, the COMSOL-based Finite Element (FE) Simulations, in conjunction with our developed theoretical model, was utilized to theoretically determine the change in drain–source resistance. This theoretically calculated ΔR_DS/R_DS(0) of 0.45% at room temperature closely aligns with the experimental observations. Moreover, the sensor exhibited a gate-bias-dependent tunability, with the enhancement of sensitivity under increasingly negative gate voltages. Furthermore, the sensors demonstrated a stable and repeatable sensing operation over multiple pressure cycles up to 300 °C, with a rapid response time of <10 ms, suggesting excellent potential for reliable, high-performance pressure sensing in harsh, high-temperature environments. Full article

In this study, the optical gain characteristics of a green laser sample based on a III-Nitride InGaN single-quantum-well structure were investigated. The Green gap phenomenon, caused by bandgap fluctuations due to inhomogeneous indium composition and the quantum-confined Stark effect (QCSE), has been a major obstacle in achieving high efficiency and high output in green-light-emitting devices. To address these issues, a sample grown on a (0001)-oriented GaN substrate with a single-quantum-well active layer was fabricated to suppress In composition non-uniformity and enhance the overlap of electron and hole wavefunctions. The optical gain behavior was analyzed using the Variable Stripe Length Method (VSLM) under various excitation densities and stripe lengths ($L_{cav}$). The results showed that as the stripe length increased, the spectral linewidth decreased and stimulated emission occurred at lower excitation densities. However, excessive cavity length led to gain saturation and a red shift in the peak wavelength due to Joule heating effects. These findings provide essential insights for determining the optimal cavity length in laser diode fabrication and are expected to serve as fundamental guidelines for improving the efficiency and output power of III-Nitride-based green laser diodes. Full article

Gallium nitride (GaN) has emerged as one of the most promising wide-bandgap semiconductors for next-generation space photovoltaics. In contrast to conventional III–V compounds such as GaAs and InP, which are highly efficient under terrestrial conditions but suffer from radiation-induced degradation and thermal instability, GaN offers an exceptional combination of intrinsic material properties ideally suited for harsh orbital environments. Its wide bandgap, high thermal conductivity, and strong chemical stability contribute to superior resistance against high-energy protons, electrons, and atomic oxygen, while minimizing thermal fatigue under repeated cycling between extreme temperatures. Recent progress in epitaxial growth—spanning metal–organic chemical vapor deposition, molecular beam epitaxy, hydride vapor phase epitaxy, and atomic layer deposition—has enabled unprecedented control over film quality, defect densities, and heterointerface sharpness. At the device level, InGaN/GaN heterostructures, multiple quantum wells, and tandem architectures demonstrate outstanding potential for spectrum-tailored solar energy conversion, with modeling studies predicting efficiencies exceeding 40% under AM0 illumination. In this review article, the current state of knowledge on GaN materials and device architectures for space photovoltaics has been summarized, with emphasis placed on recent progress and persisting challenges. Particular focus has been given to defect management, doping strategies, and bandgap engineering approaches, which define the roadmap toward scalable and radiation-hardened GaN-based solar cells. With sustained interdisciplinary advances, GaN is anticipated to complement or even supersede traditional III–V photovoltaics in space, enabling lighter, more durable, and radiation-hard power systems for long-duration missions beyond Earth’s magnetosphere. Full article

In recent years, polymer-based hybrid nanocomposites have emerged as promising alternatives to traditional heavy metal shields due to their low density, flexibility, and environmental safety. In this study, the synthesis of PS-PEG copolymers and the gamma radiation-shielding properties of PS-PEG/As₂O₃, PS-PEG/BN, and PS-PEG/As₂O₃/BN nanocomposites with different compositions are investigated. The goal is to find the optimal nanocomposite composition for gamma radiation shielding and dosimetry. Therefore, the mass attenuation coefficient (MAC), linear attenuation coefficient (LAC), half-value layer (HVL), tenth-value layer (TVL), effective atomic number, mean free path (MFP), radiation shielding efficiency (RPE), electron density, and specific gamma-ray constant were presented. Gamma rays emitted by the Eu source were detected by a high-purity germanium (HPGe) detector device. GammaVision was used to analyze the given data. Photon energy was in the vicinity of 121.8–1408.0 keV. The MAC values in XCOM simulation tools were used to compute. Gamma-shielding efficiency was increased by an increased number of NPs at a smaller photon energy. At 121.8 keV, the HVL of a composite with 70 wt% As₂O₃ NPs is 2.00 cm, which is comparable to the HVL of lead (0.56 cm) at the same energy level. Due to the increasing need for lightweight, flexible, and lead-free shielding materials, PS-b-PEG copolymer-based nanocomposites reinforced with arsenic oxide and BN NPs will be materials of significant interest for next-generation radiation protection applications. Full article

High-nitrogen austenitic stainless steels (HNASS) require compositional strategies that simultaneously maximize corrosion resistance and microstructural stability while suppressing delta (δ) ferrite and deleterious precipitates. Here, an explainable multi-objective design workflow is developed that couples thermodynamic descriptors from the Calculation of Phase Diagrams (CALPHAD) approach—using both equilibrium and Scheil solidification calculations—with machine learning surrogate models, random forest (RF) and Extreme Gradient Boosting (XGBoost), trained on 60,480 compositions in the Fe–C–N–Cr–Mn–Mo–Ni–Si space. The physics-informed feature set comprises phase fractions; transformation and precipitation temperatures for δ-ferrite, chromium nitride (Cr₂N), sigma (σ) phase and M₂₃C₆ carbides; liquidus and solidus temperatures; and the pitting-resistance equivalent number (PREN). The RF model achieves consistently low prediction errors, with a PREN root-mean-square error (RMSE) of ≈0.004, and exhibits strong generalization. Shapley additive explanations (SHAP) reveal metallurgically consistent trends: increasing nitrogen (N) suppresses δ-ferrite and promotes Cr₂N; carbon (C) promotes M₂₃C₆; molybdenum (Mo) promotes the σ-phase; and C and silicon (Si) widen the freezing range. Using the trained surrogate as the objective evaluator, the non-dominated sorting genetic algorithm III (NSGA-III) builds Pareto fronts that minimize the δ-ferrite range, Cr₂N, σ-phase, M₂₃C₆ and the freezing range (ΔT) while maximizing PREN. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is then applied to rank the Pareto-optimal candidates and to select compositions that combine elevated PREN with controlled precipitation windows. This workflow is efficient, reproducible and interpretable and provides actionable composition candidates together with a transferable methodology for data-driven stainless steel design. Full article

The development of metal nanostructures on large-area Gallium Nitride (GaN) surfaces has the potential to enable new, low-cost technologies for III-N semiconductor layer nanostructuring. Self-assembled nanostructures are typically formed through the thermal activation of solid-state dewetting (SSD) in thin metal layers. However, such thermal processing can induce degradation of the metal-GaN material system. This comprehensive study investigated the thermal stability of thin metal films on GaN surfaces, focusing on their morphology and nanostructuring for high-temperature processing. The research expands and systematizes the understanding of the thin metal layers on GaN surface interactions at high temperatures by categorizing metals based on their behaviour: those that exhibit self-assembly, those that catalyze GaN decomposition, and those that remain thermally stable. Depending on the annealing temperature and metal type, varying degrees of GaN layer decomposition were observed, ranging from partial surface modification to significant volumetric degradation of the material. A wide range of metals was investigated: Au, Ag, Pt, Ni, Ru, Mo, Ti, Cr, V, Nb. These materials were selected based on criteria such as high work function and chemical resistance. In this studies metal layers with a target thickness of 10 nm deposited by vacuum evaporation on 2.2 $\mathsf{\mu }$m thick GaN layers grown by metal organic vapor phase epitaxy were applied. The surface morphology and composition were analyzed using AFM, SEM, EDS, and Raman spectroscopy measurement techniques. Full article

It is important to develop a tetracycline (TC) detection method with a simple synthesis method, high sensitivity, and fast detection speed. Herein, a novel sensor was designed using europium-doped boron nitride (BN-Eu) for evaluation on tetracycline (TC). BN-Eu was synthesized by a simple one-step hydrothermal method. Based on the dual-emission fluorescence signal characteristics of BN-Eu, the content of tetracycline was detected by ratio fluorescence sensing. When the TC concentration increased, the fluorescence emission of BN at 449 nm remained nearly constant, the characteristic emission peak of Eu³⁺ at 618 nm was enhanced due to the antenna effect(AE). The ratiometric fluorescence detection of TC in the range of 0.010–1.0 μmol L⁻¹ was achieved with a detection limit of 4.0 nmol L⁻¹. In addition, the detection system underwent a color shift from blue to red under an irradiation of 365 nm as the TC concentration increased. Based on this, TC visual detection was achieved. The colorimetric signal versus the concentration of TC in the range from 0 to 50 μmol L⁻¹ had a good linear relationship with a detection limit of 1.4 μmol L⁻¹. The probe showed good detection performance through the determination of tetracycline content in tetracycline ointment. The prepared BN-Eu probe has fast response, good sensitivity to TC, and has good potential in detecting tetracycline content in complex samples. Full article

Thermal cycling test is one of the reliability tests, which are important for metal-ceramic layered composites (metallized ceramic substrates), a part in power modules. Since thermal cycles are within a large range of temperature, the test has only been performed using a thermal chamber. It limited the understanding of degradation mechanism in metallized ceramics substrates. Among NDE techniques, Digital Image Correlation (DIC) is a simple and effective method, enhanced by modern digital imaging technologies, enabling precise measurements of displacement, strain, deformation, and defects with a simple setup. In this paper, we combined some of our previous work to make a review to present a full analysis of a silicon metallized substrate under thermal cycling test (from beginning to fail) using DIC method. The main content is the application of DIC in evaluating the reliability of metallized silicon nitride (AMB-SN) substrates under thermal cycling with temperatures from −40 °C to 250 °C. Three key aspects of the AMB-SN substrate are presented, including (i) thermal strain characteristics before and after delamination, (ii) warpage and dynamic bending behavior across damage states, and (iii) stress–strain behavior of constituent materials. The review provides insights into degradation progress of the substrate and the role of Cu in substrate failure, and highlights DIC’s potential in ceramic composites, offering a promising approach for improving reliability test simulations and advancing digital transformation in substrate evaluation, ultimately contributing to enhanced durability in high-power applications. Full article

Aluminum nitride (AlN), a III-V wide-bandgap semiconductor, has attracted significant attention for high-temperature and high-power applications. However, achieving p-type doping in AlN remains challenging. In this study, p-type AlN thin films were fabricated via magnetron sputtering using Mg-Al alloy targets with varying Mg concentrations (0.01 at.%, 0.02 at.%, and 0.5 at.%), followed by ex situ high-temperature annealing to facilitate Mg diffusion and electrical activation. The structural, morphological, and electrical properties of the films were systematically characterized using X-ray diffraction (XRD), white light interferometry (WLI), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), and Hall effect measurements. The results demonstrate that at a Mg doping concentration of 0.02 at.%, the films exhibit optimal crystallinity, uniform Mg distribution, and a favorable balance between carrier concentration and mobility, resulting in effective p-type conductivity. Increasing Mg doping leads to higher surface roughness and the formation of columnar and conical grain structures. While high Mg doping (0.5 at.%) significantly increases carrier concentration and decreases resistivity, it also reduces mobility due to enhanced impurity and carrier–carrier scattering, negatively impacting hole transport. XPS and EDS analyses confirm Mg incorporation and the formation of Mg-N and Al-Mg bonds. Overall, this study indicates that controlled Mg doping combined with high-temperature annealing can achieve p-type AlN films to a certain extent, though mobility and carrier activation remain limited, providing guidance for the development of high-performance AlN-based bipolar devices. Full article