Mehedi Hasan Tanim

Reflection high‐energy electron diffraction (RHEED) is an in situ probe for monitoring surface evolution during molecular beam epitaxy (MBE), yet coupling future‐pattern prediction with downstream recognition remains limited. Here, we present PredRHEED, a cascaded deep‐learning framework that combines RHEED‐pattern classification with future‐frame prediction during scandium aluminum nitride (ScAlN) growth in MBE. The framework combines a hybrid classifier composed of convolutional neural network (CNN) and Transformer, in which CNN extracts local diffraction features and Transformer encoder captures their global arrangement, to identify three RHEED‐pattern classes, streaky, transition, and spotty, while the prediction module employs a memory‐enhanced self‐attention convolutional long short‐term memory (MSAM‐ConvLSTM) predictor to forecast future RHEED frames. During inference, the predictor uses the preceding 15 s of RHEED data to predict the evolution of the RHEED pattern over the next 5 s. The predicted frames are then classified to determine the anticipated RHEED‐pattern class. Using 22,110 RHEED images acquired during a single continuous ScAlN growth experiment, the classification branch achieved 93.68% accuracy, whereas the prediction branch generated future frames with high structural fidelity. Across 50 classifier‐adaptation epochs, the maximum observed test‐set accuracy was 84.7% at epoch 11, while accuracy at the final epoch was 82.7%. The epoch‐wise test‐set trajectory is exploratory.

We report the molecular beam epitaxy and structural characterization of single-phase wurtzite LaxAl1−xN thin films, with a La composition as high as x=0.20. In situ reflection high-energy electron diffraction confirms epitaxial film formation, and atomic force microscopy reveals sub-nanometer surface roughness for all compositions investigated. High-resolution x-ray diffraction and scanning transmission electron microscopy further confirm c-axis orientation, high crystalline quality, and precise in-plane epitaxial alignment. Importantly, atomic-resolution structural analysis demonstrates a continuous decrease in the c/a lattice-parameter ratio with increasing La content. In addition, out-of-plane piezoresponse force microscopy measurements show an enhanced effective d33, increasing from 5.00 pm/V for AlN to 7.66 pm/V for La0.20Al0.80N. These results establish LaAlN as a promising new wurtzite nitride alloy platform for future wide bandgap electronics, optoelectronics, and quantum photonics.

Understanding strain relaxation during the initial stages of heteroepitaxy is essential for controlling interfacial structure and film quality, yet direct real-time quantification remains difficult. Here, we report on the demonstration of AutoRHEED, an AI-assisted in situ framework for tracking subnanometer strain relaxation during epitaxial growth. The method integrates image quality filtering, autonomous streak identification, and physics-guided geometric calibration to directly extract quantitative in-plane interplanar spacing (d spacing) evolution from raw reflection high-energy electron diffraction (RHEED) videos. We applied the framework to highly lattice-mismatched AlSb/Si(001) growth and demonstrated that AutoRHEED could capture the transient evolution from the initially strained state to full relaxation with monolayer-level sensitivity. Moreover, the in situ-derived relaxation trajectory shows excellent agreement with ex situ HAADF-STEM, confirming its structural fidelity and temporal reliability.

We report molecular beam epitaxy and ferroelectric properties of Al1-xYxN thin films with Y composition up to x = 41%. Structural characterization reveals that a wurtzite lattice structure is well preserved despite the large lattice distortions induced by increasing Y content. Both the coercive field and remanent polarization show a strong dependence on Y composition. The coercive field varies from 5.5 to 2.8 MV/cm with increasing Y compositions from 10% to 41%, whereas the remanent polarization is reduced from 140 to 70 μC/cm2. These properties are further compared with previously reported AlScN and GaScN. This study establishes AlYN as a tunable ferroelectric ultrawide-bandgap semiconductor for next-generation electronic, photonic, and electromechanical devices.

In this study, we present a systematic optimization of 10 nm GaSb thin film grown directly on Si(001) substrate using a 5 nm AlSb buffer layer. By carefully tuning the AlSb buffer layer's growth temperature and thickness, growth conditions of 300 °C and 5 nm are identified that yield a smooth, two-dimensional 10 nm GaSb morphology with a root-mean-square (r.m.s.) surface roughness of 0.90 nm and an X-ray diffraction (XRD) full width at half-maximum (FWHM) of 0.76°. Cross-sectional transmission electron microscopy confirms the high-quality AlSb/GaSb interface and a minimal level of defect propagation through AlSb. In addition, micro-Raman spectroscopy and temperature-dependent Hall measurements reveal a slightly strained GaSb layer with a room-temperature hole mobility of approximately 350 cm²/(V·s). Furthermore, increasing the GaSb thickness to 300 nm improves surface quality and crystallinity, achieving an r.m.s. roughness of 0.40 nm and an FWHM of 0.39°. These results demonstrate the viability of integrating ultrathin, high quality GaSb layers on Si(001), showing their potential for scalable, high performance applications in next-generation CMOS-compatible micro/nanoelectronic devices.

Brain-inspired neuromorphic computing systems require hardware components analogous to biological neurons and synapses. Honey based natural organic memristor has demonstrated promising nonvolatile memristive behaviors, with the advantages of sustainability, environmentally friendliness, and low-cost manufacturing. In this study, carbon nanotubes (CNTs) are added in honey to fabricate honey-CNT memristive artificial synaptic devices. Honey-CNT film is characterized by micro-Raman spectroscopy and the distribution of CNT bundles embedded in the honey-CNT composite layer by cross-sectional scanning electron microscopy for the first time. Critical synaptic functions of the honey-CNT memristor, including spike-rate-dependent plasticity, spike voltage dependent plasticity, learn-forget-relearn, and supralinear spatial summation are revealed, which have not been reported by honey based memristive devices before. Paired pulse facilitation with a PPF index as large as 4.5 is observed, indicating the enhancement of synaptic weight by CNTs. Furthermore, honey-CNT memristor based neuromorphic system is evaluated in terms of linearity, accuracy, read/write energy, and overall performance by the image recognition using Stochastic Gradient Descent and Adaptive Moment Estimation learning algorithms and the Modified National Institute of Standards and Technology database.

Given its strong electro-optic and optical nonlinearities as well as CMOS compatibility, scandium-alloyed aluminum nitride (ScAlN) stands out as a material with transformative potential for next-generation integrated photonics. A comprehensive understanding of its nonlinear characteristics is critical for developing practical nonlinear optical devices and fully integrated photonic systems. In this work, we experimentally and computationally investigate the second-order nonlinear properties of epitaxial ScAlN thin films grown by molecular beam epitaxy across a range of scandium concentrations (0%–30%). We report a 17-fold increase in the d31 coefficient compared to aluminum nitride, reaching 2.59 pm/V at 30% Sc at 1266 nm while shorter wavelengths and larger Sc concentrations are needed to increase d33. Our two independent first-principles calculations verify these qualitative trends. With its enhanced second-order nonlinearities, the ScAlN material class holds promise for enabling efficient type-I/II nonlinear interactions in modulators, frequency converters, and entangled photon sources.

The strong polarization fields present at the AlN/GaN heterointerface make them an attractive candidate for the development of high electron mobility transistors (HEMTs) with high current densities. In this work, we report exceptionally high two-dimensional electron gas (2DEG) density in AlN/GaN heterostructures grown by plasma-assisted molecular beam epitaxy. The sample with a 9 nm AlN barrier, near the onset of relaxation, yields a maximum 2DEG density of ∼1.3 × 1014 cm−2, more than 2× larger than previously reported values, while the fully strained 6 nm barrier exhibits ∼7.8 × 1013 cm−2 with superior crystalline quality. Additionally, the sheet resistance values reported in this work are below 200 Ω/□ at 2DEG densities approaching 1014 cm−2. These results highlight the critical role of strain–polarization coupling in achieving extreme carrier confinement, establishing benchmarks for III-nitride HEMTs and future wide-bandgap electronics.