Results 171 to 180 of about 276,670 (296)

A Solution for Exosome‐Based Analysis: Surface‐Enhanced Raman Spectroscopy and Artificial Intelligence

Advanced Intelligent Discovery, EarlyView.
Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz, Zakarya Al‐Shaebi, Omer Aydin   +2 more
wiley   +1 more source

Unveiling the roles of device structure and driving frequency in mitigating crosstalk effects in nanopixel light-emitting displays. [PDF]

Microsyst Nanoeng
Li W, Zhang S, Zhou X, Zhang Y, Guo T, Wu C.   +5 more
europepmc   +1 more source

Application of Neural Networks for Advanced Ir Spectroscopy Characterization of Ceria Catalysts Surfaces

Advanced Intelligent Discovery, EarlyView.
A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali, Lachlan Caulfield, Eric Sauter, Alexei Nefedov, Chengwu Yang, Christof Wöll   +5 more
wiley   +1 more source

Pixel level anomaly detection in second harmonic generation microscopy for non destructive defect inspection of AlGaN/GaN heterostructures. [PDF]

Discov Nano
Kang CF, Hung CC, Huang CH, Li TC, Uen WY, Chiu CH.   +5 more
europepmc   +1 more source

Achieving Avalanche in GaN-on-silicon Diodes

International audienceAlthough qualified up to 650 V voltage operation, lateral GaN devices are subject to severe limitations for higher voltage applications such as a large device size, surface trap related reliability concerns or the absence of ...
Medjdoub, F
core  

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Advanced physical modeling approaches for high-precision TCAD simulation of GaN HEMT power devices: a review. [PDF]

Discov Nano
Zhao H, Firdaus A, Farizuan M, Tan WH, Kawarada H, Falina S, Syamsul M.   +6 more
europepmc   +1 more source

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source

Epitaxial n-ZnO/MoS₂/p-GaN Heterostructure Light-Emitting Diodes. [PDF]

Nano Lett
Rahmatulloh I, Dalayoan DJC, Ali A, Shin S, Nguyen ATD, Kwon T, Behera S, Lee J, Kim H, Jeong HY, Namgung S, Yi GC, Chung K.   +12 more
europepmc   +1 more source

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source