Results 91 to 100 of about 384,953 (220)
This study presents a graphene oxide‐based gas sensor array integrated with a deep learning framework for precise detection and classification of multiple gases. By combining advanced sensing materials and a 1D‐ResNet architecture, the system achieves high sensitivity and accuracy, demonstrating its potential for real‐time environmental monitoring ...
Tianci Liu+5 more
wiley +1 more source
Facilitating crRNA Design by Integrating DNA Interaction Features of CRISPR‐Cas12a System
This study introduces a novel approach combining molecular dynamics simulations and neural network modeling to predict the Cas12a trans‐cleavage activity. By integrating sequence and molecular interaction features, prediction accuracy is enhanced, and identify key features affecting Cas12a trans‐cleavage activity.
Zhihao Yao+7 more
wiley +1 more source
This study presents a highly reliable gas sensor platform featuring SnO2 nanonetworks functionalized with Au and Pd nanocatalysts. Enhanced stability and optimized performance enable over 99.5% classification accuracy in deep learning, even under extreme conditions.
Yun‐Haeng Cho+15 more
wiley +1 more source
The presence of a micropapillary (MPP) component is critical for lung adenocarcinoma (LUAD) surgery, yet reliable blood biomarkers remain lacking. This study integrates proteomics for biomarker identification, a nanomixing‐enhanced surface‐enhanced Raman spectroscopy (SERS) platform for sensitive detection, and machine learning for accurate ...
Dechun Zhang+4 more
wiley +1 more source
Reconstructing Three‐Dimensional Optical Anisotropy with Tomographic Müller‐Polarimetric Microscopy
Tomographic Müller polarimetric microscopy is a novel imaging technique that resolves 3D birefringent properties of bulky samples, unveiling hierarchical nanostructures at microscopic resolution. Based on incoherent visible‐light polarimetry, it achieves experimental simplicity by eliminating phase measurements.
Yang Chen+4 more
wiley +1 more source
This work explores a machine learning (ML) model with electrochemical impedance spectroscopy (EIS) data to address two critical challenges in Lithium metal batteries (LMBs): capacity degradation trajectory and knee point (KP) estimation, for the first time.
Qianli Si+4 more
wiley +1 more source
This study presents an explainable multimodal AI model, MAIGGT (Multimodal Artificial Intelligence Germline Genetic Testing), that combines whole‐slide histopathology with clinical data for accurate germline BRCA1/2 mutation prescreening. By integrating digital pathology and EHR phenotypes, MAIGCT enables cost‐effective, scalable hereditary breast ...
Zijian Yang+23 more
wiley +1 more source
This work presents a critical evaluation of the empirical Thornton's structure zone diagram, a cornerstone in predicting thin film microstructure. Through transmission electron microscopy, we observe that Sn─O thin films form nanosized dendrites, which are not expected according to the structure zone diagram.
Denis Music+5 more
wiley +1 more source
An in situ characterization platform is established for water management and fault diagnosis in AEMFCs by employing the relaxation time method to analyze electrochemical impedance spectra. This approach identifies the characteristic frequency ranges of ionic, charge, and reactant transport resistances, enabling quantitative diagnosis of water transport
Haodong Huang+9 more
wiley +1 more source
Computational and AI‐Driven Design of Hydrogels for Bioelectronic Applications
This review highlights the role of AI in advancing hydrogel design for bioelectronics, exploring natural, and synthetic gels tailored for applications like wound healing, biosensing, and tissue engineering. It emphasizes the synergy between hydrogels, electronics, and AI in creating responsive, multifunctional systems, showcasing recent innovations ...
Rebekah Finster+2 more
wiley +1 more source