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arXiv 2025年

作者： Shafiee, Amin Chen, Linhong Pasricha, Sudeep Yao, Jie Nikdast, Mahdi Department of Electrical and Computer Engineering Colorado State University Fort CollinsCO United States Department of Materials Science and Engineering University of California BerkeleyCA United States

We present a silicon-photonic tensor core using 2D ferroelectric materials to enable wavelength- and polarization-domain computing. Results, based on experimentally characterized material properties, show up to 83% im... 详细信息

关键词： Polarization

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MatGNet: A graph neural network for crystal property prediction as an alternative to first-principles calculations

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materials Today Communications 2025年 44卷

作者： Teng, Pandi Fu, Chengyu Shen, Shiru Zang, Huaijuan Fang, Jing Ren, Yongsheng Zhan, Shu School of Computer and Information Engineering Hefei University of Technology Hefei China School of Materials Science and Engineering Hefei University of Technology China Department of Information Engineering Anhui Electrical Engineering School Hefei230011 China Faculty of Metallurgical and Energy Engineering Kunming University of Science and Technology Kunming China

Deep learning techniques are increasingly prevalent in predicting the properties of periodic crystalline materials, gradually emerging as a powerful alternative to time-consuming and computationally intensive first-principles calculations. To this end, we innovatively propose a new model, the Graph Convolutional Neural Network, based on Mat2vec Atomic Embeddings for Crystals (MatGNet). Our model represents crystalline structures as graph structures, where node features are encoded using the Mat2vec atomic embedding method and integrated with atomic coordinate information. On the other hand, edge features comprehensively reflect interatomic interactions by incorporating Gaussian distances between atoms expanded using radial basis functions. Additionally, we have optimized the model better to characterize the angular features of crystals' structural embeddings and enhance crystalline structures' representational capacity. The network architecture of the MatGNet model is an improved gated convolutional network with a self-attention mechanism, enabling efficient updating and propagation of node and edge information on graph structures. Experiments on the JARVIS-DFT dataset demonstrate that our method excels in predicting the properties of crystalline materials, with accuracy surpassing previous models. This approach provides an efficient and accurate solution for predicting the properties of crystalline materials, potentially accelerating the rapid development of crystalline material research. © 2025 Elsevier Ltd

关键词： Prediction models

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Development of open-architecture two-wavelength grayscale digital light processing for advanced vat photopolymerization

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Additive Manufacturing 2025年 107卷

作者： Zhang, Heyang Maier, Abby Mathews, Melvin Hu, Jingtong Zhao, Xiayun Department of Mechanical Engineering and Materials Science University of Pittsburgh PittsburghPA United States Department of Electrical and Computer Engineering University of Pittsburgh PittsburghPA United States Engineering Quantum Systems Massachusetts Institute of Technology CambridgeMA United States

Vat photopolymerization (VPP) is an additive manufacturing technique that creates 3D parts by projecting 2D images onto layers of photopolymer resin. These images are often delivered using digital light processing (DLP) systems with digital micromirror devices. While conventional VPP relies on a single-wavelength DLP system, recent advancements have introduced multi-wavelength approaches to selectively trigger distinct photochemical reactions, enhancing multi-material printing and geometric precision. To further advance multi-wavelength VPP, open-architecture two-wavelength DLP systems are essential for enabling real-time control with adaptive exposure masks. In this work, we develop an orthogonal two-wavelength grayscale DLP system featuring custom optics and a reconfigured field-programmable gate array (FPGA)-based control circuit. The system integrates a 50/50 beam-splitting optical architecture that merges 365 nm and 460 nm light sources, ensuring minimal distortion and precise alignment. A high-resolution CMOS camera and power meter are used to quantify the accuracy and alignment of the two-wavelength exposure masks. A workflow for projection alignment and calibration, grayscale image generation, compensation, and bit-stream data transmission via FPGA programming is established, enabling high-resolution, precisely aligned, and spatially accurate two-wavelength grayscale intensity projections onto the build platform. The system's performance is validated through ray-tracing simulations, optical characterizations, and experimental sample printing. The developed architecture facilitates integration with mechanized platforms, metrology tools, and process control technologies, providing a robust foundation for reproducible and precise two-wavelength VPP. The elaborate methodologies of optics design, FPGA programming, and image processing advance both existing and emerging multi-wavelength VPP technologies, enhancing their capability for complex material systems and

关键词： Ray tracing

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Advancing athermal silica fiber lasers to watt-level power and beyond 7

Advancing athermal silica fiber lasers to watt-level power a...

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Photonic Heat Engines: science and Applications VII 2025

作者： Chen, Chun-Wei Balliu, Enkeleda Meehan, Bailey Hawkins, Thomas W. Ballato, John Dragic, Peter D. Boilard, Tommy Bernier, Martin Digonnet, Michel J.F. Edward L. Ginzton Laboratory Stanford University StanfordCA94305 United States Cobolt AB HÜBNER Photonics Solna171 54 Sweden Department of Materials Science and Engineering Clemson University SC United States Department of Electrical Computer Engineering University of Illinois at Urbana-Champaign IL United States Université Laval Québec Canada

ISBN: (数字)9781510685079

ISBN: (纸本)9781510685062

Waste heat in fiber lasers poses major challenges in frequency, power, and pointing stabilities, as well as beam quality and power scaling. Using anti-Stokes-fluorescence cooling, we developed a radiation-balanced Yb-doped silica fiber amplifier with a novel aluminophosphosilicate core-glass composition that delivers 575 mW with no net internal heat generation by amplifying a 0.9-mW seed at 1064 nm (28.0 dB of gain). With a lower seed power (0.4 mW), a radiation-balanced gain of 31.5 dB was achieved. We discuss the strategies and recent progress in silicate-glass engineering that enabled this breakthrough performance in a small-core fiber at atmospheric pressure, as well as the potential for power-scaling radiation-balanced fiber lasers to the 100-watt level through advanced fiber designs. Our findings point to a promising path for stable high-power operation free from thermal limitations. © 2025 SPIE.

关键词： Laser cooling

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Atomic Insights into Strain-Induced Nanoscopic Compositional Fluctuation in AlGaN Quantum Well Epitaxy

SSRN

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SSRN 2025年

作者： Huang, Chia-Yen Chao, Ying-Chun Huang, Cheng-Yao Yen, Hung-Wei Department of Photonics College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Department of Materials Science and Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei Taiwan Department of Materials Science and Engineering

Two identical UVC light-emitting diode AlGaN epitaxy were grown on high-quality AlN buffer layers with different strain states. We characterized the AlGaN epi by high-resolution scan transmission electron microscopy (HR-STEM) and atom probe tomography (APT). Geometry phase analysis with HR-STEM revealed the sample grown on the more compressively strained template possesses a more pronounced local lattice constant distortion in the multiple-quantum-well (MQW) region. APT further verified the local lattice distortion originated from the strain-induced Ga segregation in the MQW. The comparative compositional analysis revealed the nanoscopic compositional fluctuation favors further incorporation of Ga during epitaxial growth, which triggered the AlGaN growth front destabilization and new defect nucleation. The 1-D composition profiling from both electron dispersive microscopy and APT suggested nitrogen desorption during the AlGaN stress relaxation. © 2025, The Authors. All rights reserved.

关键词： Stress relaxation

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Radiation-Resilient Amorphous Indium Oxide FEFETs for Embedded Nonvolatile Memory

Radiation-Resilient Amorphous Indium Oxide FEFETs for Embedd...

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Annual International Symposium on Reliability Physics

作者： Sharadindu Gopal Kirtania Faaiq G. Waqar Dyutimoy Chakraborty Jaewon Shin E. Sarkar Justin Reiss Jason Dean Yeager Douglas E. Wolfe Shimeng Yu Suman Datta School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta Georgia USA Department of Materials Science and Engineering Pennsylvania State University State College Pennsylvania USA

ISBN: (数字)9798331504779

ISBN: (纸本)9798331504786

We report the first-ever study on the radiation resilience of a back-end-of-line (BEOL) compatible W-doped Indium Oxide (IWO) ferroelectric field-effect transistor (FEFET) under neutron irradiation. The findings demonstrate remarkable resilience of both Hf 0.5 Zr 0.5 O 2 (HZO) ferroelectric capacitors (FECAPs) and IWO FEFETs to neutron irradiation. Subjected to neutron irradiation at fluences up to 10 15 n/cm 2 , HZO FECAPs maintain stable remnant polarization (2P r ) and coercive voltage (2V c ) up to 10 11 cycles without any breakdown. The IWO FEFETs show robust switching performance and exhibit minimal degradation in memory window (MW) and read current window (CW). Importantly, the retention and endurance performance remain stable after neutron radiation exposure, without significant failure. Destiny simulations were performed to assess the impact of radiation on the system-level performance of an 8 MB 1T-1FEFET-based embedded RAM at the 32 nm node. The results showed negligible effects on read latency and only a minor 0.36% increase in dynamic read energy at a neutron fluence of 10y15 n/cm 2 . The combination of high performance, non-volatility, and radiation hardness makes IWO FEFETs a promising candidate for high-density, persistent memory applications in radiation-rich environments.

关键词： Degradation Radiation effects Nonvolatile memory Random access memory Neutrons Indium Transistors FeFETs Resilience Switching circuits

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Enhancing Long-range Dependency with State Space Model and Kolmogorov-Arnold Networks for Aspect-based Sentiment Analysis 31

Enhancing Long-range Dependency with State Space Model and K...

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31st International Conference on Computational Linguistics, COLING 2025

作者： Lawan, Adamu Pu, Juhua Yunusa, Haruna Umar, Aliyu Lawan, Muhammad School of Computer Science and Technology Beihang University Beijing China National Research Institute for Teaching Materials in Information Science and Tech. China School of Automation Science and Electrical Engineering Beihang University Beijing China School of Computing University of Portsmouth Portsmouth United Kingdom Department of Information and Communication Technology Federal University Gusau Nigeria

ISBN: (纸本)9798891761964

Aspect-based Sentiment Analysis (ABSA) evaluates sentiments toward specific aspects of entities within the text. However, attention mechanisms and neural network models struggle with syntactic constraints. The quadratic complexity of attention mechanisms also limits their adoption for capturing long-range dependencies between aspect and opinion words in ABSA. This complexity can lead to the misinterpretation of irrelevant contextual words, restricting their effectiveness to short-range dependencies. To address the above problem, we present a novel approach to enhance long-range dependencies between aspect and opinion words in ABSA (MambaForGCN). This approach incorporates syntax-based Graph Convolutional Network (SynGCN) and MambaFormer (Mamba-Transformer) modules to encode input with dependency relations and semantic information. The Multihead Attention (MHA) and Selective State Space model (Mamba) blocks in the MambaFormer module serve as channels to enhance the model with short and long-range dependencies between aspect and opinion words. We also introduce the Kolmogorov-Arnold Networks (KANs) gated fusion, an adaptive feature representation system that integrates SynGCN and MambaFormer and captures non-linear, complex dependencies. Experimental results on three benchmark datasets demonstrate MambaForGCN's effectiveness, outperforming state-of-the-art (SOTA) baseline models. © 2025 Association for Computational Linguistics.

关键词： Semantics

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Interactions of Light, Surface Plasmons and Excitons in Bilayers of FAPbI3 Nanocrystals with Core-Shell Au/SiO2 Nanoparticles

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ACS Photonics 2025年第5期12卷 2344-2355页

作者： Souzou, Aliki Athanasiou, Modestos Manoli, Andreas Constantinou, Marios Bodnarchuk, Maryna I. Kovalenko, Maksym V. Andreou, Chrysafis Itskos, Grigorios Experimental Condensed Matter Physics Laboratory Department of Physics University of Cyprus Nicosia1678 Cyprus Nanotechnology Imaging and Detection Laboratory Department of Electrical and Computer Engineering University of Cyprus Nicosia2112 Cyprus Institute of Inorganic Chemistry Department of Chemistry and Applied Biosciences ETH Zürich ZürichCH-8093 Switzerland Laboratory for Thin Films and Photovoltaics Empa─Swiss Federal Laboratories for Materials Science and Technology Überlandstrasse 129 DübendorfCH-8600 Switzerland

Integration of plasmonic nanostructures into perovskites is an effective way to enhance and tailor light-matter interactions, resulting in further improvement of the already impressive intrinsic photonic properties of the perovskites. Despite remarkable recent progress, the complex mechanisms via which light, excitons and plasmons interact in such hybrid structures are not fully understood. Herein, plasmonic-perovskite structures in bilayer configuration are produced by the deposition of formamidinium lead triiodide (FAPbI3) nanocrystals (NCs) on top of a core-shell gold-silica (Au/SiO2) nanoparticle (NP) underlayer. By tuning the NP core and shell size, a 5-fold enhancement of the macroscopic absorption and luminescence in the vicinity of the localized surface plasmon (LSP) resonance can be achieved in the bilayers compared to reference, pristine FAPbI3 NCs films. Optical spectroscopy performed both at the ensemble and at the few particle level, supported by numerical simulations allow to disentangle the contributions of near-field LSP-exciton and far-field LSP-light interactions that result in the enhancement of the light absorption and light emission. Based on our results, far field light scattering by the LSP results in photon recycling within the perovskite NCs layer, effectively increasing light absorption and light emission. Near-field energy transfer from the metal NPs to the semiconductor NCs contributes less but becomes significant for the case of large core and small shell NPs due to the increased spectral overlap and closer proximity of the surface plasmons and excitons, respectively. © 2025 The Authors. Published by American Chemical Society.

关键词： Surface plasmon resonance

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Robust Flower Cluster Matching Using The Unscented Transform

arXiv

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arXiv 2025年

作者： Chu, Andy Shrestha, Rashik Gu, Yu Gross, Jason N. Department of Mechanical Materials and Aerospace Engineering West Virginia University Morgantown United States Lane Department of Computer Science and Electrical Engineering West Virginia University Morgantown United States

Monitoring flowers over time is essential for precision robotic pollination in agriculture. To accomplish this, a continuous spatial-temporal observation of plant growth can be done using stationary RGB-D cameras. However, image registration becomes a serious challenge due to changes in the visual appearance of the plant caused by the pollination process and occlusions from growth and camera angles. Plants flower in a manner that produces distinct clusters on branches. This paper presents a method for matching flower clusters using descriptors generated from RGB-D data and considers allowing for spatial uncertainty within the cluster. The proposed approach leverages the Unscented Transform to efficiently estimate plant descriptor uncertainty tolerances, enabling a robust image-registration process despite temporal changes. The Unscented Transform is used to handle the nonlinear transformations by propagating the uncertainty of flower positions to determine the variations in the descriptor domain. A Monte Carlo simulation is used to validate the Unscented Transform results, confirming our method’s effectiveness for flower cluster matching. Therefore, it can facilitate improved robotics pollination in dynamic environments. Copyright © 2025, The Authors. All rights reserved.

关键词： Image registration

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electrical and structural Properties of in-situ MOCVD Grown Al2O3/β-Ga2O3 and Al2O3/β-(AlxGa1-x)2O3 MOSCAPs

arXiv

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arXiv 2025年

作者： Bhuiyan, A.F.M. Anhar Uddin Meng, Lingyu Yu, Dong Su Dhara, Sushovan Huang, Hsien-Lien Vangipuram, Vijay Gopal Thirupakuzi Hwang, Jinwoo Rajan, Siddharth Zhao, Hongping Department of Electrical and Computer Engineering The Ohio State University ColumbusOH43210 United States Department of Materials Science and Engineering The Ohio State University ColumbusOH43210 United States Department of Electrical and Computer Engineering University of Massachusetts Lowell LowellMA01854 United States

In this study, we investigated the electrical and structural properties of metal-oxide-semiconductor capacitors (MOSCAPs) with in-situ metal-organic chemical vapor deposition (MOCVD)-grown Al2O3 dielectrics deposited at varying temperatures on (010) β-Ga2O3 and β-(AlxGa1-x)2O3 films with different Al compositions. The Al2O3/β-Ga2O3 MOSCAPs demonstrated a significant impact of Al2O3 deposition temperature on their electrical properties as characterized by capacitance-voltage (C-V) and current-voltage (I-V) measurements. Higher deposition temperatures (900 °C) resulted in reduced voltage hysteresis (~0.3 V) and improved reverse breakdown voltage of 74.5 V with a corresponding parallel-plate electric field of EBr, Al2O3 = 5.01 MV/cm and EBr, Ga2O3 = 4.11 MV/cm under reverse bias. In contrast, lower deposition temperatures (650 °C) yielded higher voltage hysteresis (~3.44 V) and lower reverse breakdown voltage (VBr = 38.8 V with EBr, Al2O3 = 3.69 MV/cm and EBr, Ga2O3 = 2.87 MV/cm), but exhibited superior forward breakdown fields, increasing from 5.62 MV/cm at 900 °C to 7.25 MV/cm at 650 °C. High-resolution scanning transmission electron microscopy (STEM) imaging revealed a strong correlation between the deposition temperature of Al2O3 and its crystallinity. At 900 °C, Al2O3 exhibited larger crystalline regions and sharper interfaces as compared to 650 °C, contributing to improved reverse breakdown fields. For Al2O3/β-(AlxGa1-x)2O3 MOSCAPs, increasing Al composition from x = 5.5% to x = 9.2% resulted in a reduction in net carrier concentration with enhanced reverse breakdown fields, from EBr, (AlxGa1-x)2O3 = 2.55 MV/cm to 2.90 MV/cm. The reverse breakdown electric field in the Al2O3 dielectric also increased from EBr, Al2O3 = 2.41 MV/cm to 3.13 MV/cm as the Al composition increases from 5.5% to 9.2%. Forward breakdown fields of the Al2O3/β-(AlxGa1-x)2O3 MOSCAPs increased from EBr, Al2O3 = 5 MV/cm to 5.4 MV/cm with the increase of Al composition from 5.5% to 9.2%, respect

关键词： Oxide semiconductors

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