Results 91 to 100 of about 22,071 (254)

Porous Carbon Materials for Carbon Dioxide Capture

Carbon Energy, EarlyView.
This work aims to address the current status and challenges associated with the regulation of pore structures, as well as the influence of pore structures on CO2 capture. Systematic quantitative analysis of structure–property relationships, combined with machine learning approaches, can effectively evaluate the contributions of structural ...
Zhifu Liu, Chuhan Fu, Tao Qi, Hui Zhou, Guangping Hao, Yalou Guo, Guoping Hu   +6 more
wiley   +1 more source

Uniaxial compressive strength prediction and ratio parameter optimization of titanium tailings composite backfill materials using intelligent hybrid models

Deep Underground Science and Engineering, EarlyView.
Based on the 90 datasets, ERT and four optimization algorithms were used to build four hybrid models to predict the UCS of the backfill body. The SMA‐ERT model was the most effective model, and it can reliably guide the design of the backfill ratio parameters. Abstract This study analyzed the feasibility of using titanium (Ti) tailings as a backfilling
Weijun Liu, Zida Liu, Zhixiang Liu
wiley   +1 more source

Spectral efficiency optimization for millimeter wave hybrid massive MIMO systems using unsupervised learning

Intelligent and Converged Networks
Hybrid beamforming is a promising technique for massive multiple-input multiple-output (MIMO) systems because it is able to reduce the hardware cost and power consumption while improving system performance, which is considered a key enabler for the fifth-
Ziyang Huang, Maobin Tang, Wei Wang, Weiqiang Tan, Bin Tan   +4 more
doaj   +1 more source

Artificial intelligence‐assisted nanozyme design for medical and environmental applications

Journal of Intelligent Medicine, EarlyView.
AI‐assisted nanozyme design integrates cross‐source data and machine learning to enable predictive structure‐activity relationships, accelerating intelligent diagnostics, precision therapeutics, and environmental surveillance. Abstract Nanozymes, a class of nanomaterials with intrinsic enzyme‐like catalytic activities, have emerged as promising ...
Xiaolin Guo, Hao Zhang, Zihan Zhao, Qingshan Liu, Jiayi Liu, Jiang Huang, Changlong Liu, Xiaoyu Mu   +7 more
wiley   +1 more source

From Planar to 3D Nanophotonic Lenses: Advancing Design, Fabrication, and Applications

Laser &Photonics Reviews, EarlyView.
Three‐dimensional nanophotonic lenses are enabled by an integrated workflow that links design parameterization, full‐wave electromagnetic simulation, computational optimization, and freeform fabrication. This Review summarizes how these tools expand optical design freedom beyond a single patterned plane by enriching the local meta‐atom response and ...
Wei Zhu, Lyudmila V. Goncharova, Eric Johlin   +2 more
wiley   +1 more source

Artificial Intelligence for Identifying Tumor‐Reactive CD8+ T Cells: Biological Principles, Computational Advances, and Future Directions

Med Research, EarlyView.
This review details a three‐stage paradigm shift for tumor‐reactive CD8+ T‐cell identification: decoding transcriptomic states, deciphering clonal functional efficacy, and molecular‐level therapeutic TCR design. Addressing translational hurdles and generative AI “scientific blind spots”—such as missing catch bonds—we present a visionary roadmap.
Chao Yang, Yingying Sun, Yan Zhang, Yifen Shi, Zhiwen Shi   +4 more
wiley   +1 more source

Advancing Artificial Intelligence in Myopia Management: From Predicting Progression to Supporting Clinical Decisions

Med Research, EarlyView.
The AI‐enabled multimodal framework for whole‐life myopia management. Graphical abstract illustrates the transition of myopia care from premyopia to myopia, high myopia, and pathologic myopia. Multimodal data, including demographic and refractive information, genetic, behavioral and environmental factors, ophthalmic imaging, and omics profiles, can be ...
Zewei Zhang, Yun Wang, Lifei Zhang, Dongmei Chen, Weijie Zhang, Fang Li, Jibo Zhou   +6 more
wiley   +1 more source

A Dual Deep Neural Network Approach for Discriminating Internal Faults and Inrush Currents in Transformers Under CT Saturation

IEEE Access
The dependability and security of transformer differential protection can be compromised by current transformer (CT) saturation, which distorts current measurements and may lead to the maloperation of protective relays.
Sopheap Key, Soupheng Leap, Seong-Min Yoon, Heungseok Lee, Soon-Ryul Nam   +4 more
doaj   +1 more source

Machine Learning‐Assisted Prediction and Analysis of Viscosity and Fusion Characteristics for Coal and Biomass Ash

Materials Genome Engineering Advances, EarlyView.
This study develops a machine learning framework for predicting the flow temperature and viscosity of coal and biomass ash with CatBoost and LightGBM as the optimal models. Feature analysis revealed composition‐property mechanisms, and symbolic regression was further applied to derive empirical formulas for rapid and accurate prediction.
Gangcheng Wang, Muhammad Faizan, Yuanliang Li, Kun Zhou, Kaikai Li, Qi Zhang, Shulin Luo, Guixuan Wu   +7 more
wiley   +1 more source

Fault Diagnosis in an Induction‐Motor‐Driven Rotating Machinery Test Rig Under Unseen Operating Loads Using Multimodal Fusion and Multiagent Deep Reinforcement Learning

International Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT Conventional fault‐diagnosis methods, largely grounded in one‐dimensional signal analysis and linear modeling, often fail to detect complex nonlinear faults in rotating machinery operating under variable loads. Data‐driven approaches also face challenges in extracting discriminative information from high‐dimensional multisensor measurements ...
Amirreza Marzband, Javad Poshtan
wiley   +1 more source