Results 111 to 120 of about 40,795 (265)

Unveiling Exsolution‐Induced Giant Electronic and Magnetic Property Changes in Non‐Stoichiometric Titanate Perovskite Thin Films

Advanced Materials, EarlyView.
A giant insulator to metal transition and emergent superparamagnetism are revealed by nanoparticle exsolution in non‐stoichiometric titanate perovskite thin films. By combining transport, synchrotron spectroscopy, and first‐principles calculations, this work reveals how defect reconfiguration and lattice reconstruction fundamentally reshape electronic ...
Sungil Kim, June Ho Lee, Yaolong Xing, Dongchang Kim, Haeseong Jeong, Mongjun Jeong, Manuel Valvidares, Stuart S. P. Parkin, Sang Ho Oh, Donghwa Lee, Hyojin Yoon, Hyeon Han   +11 more
wiley   +1 more source

Decoupling Activation and Preservation: Architectural Design Principles of Organic Frameworks for Selective Photocatalytic Methane Oxidation

Advanced Materials, EarlyView.
Selective methane (CH4) photooxidation emerges from architectural decoupling of activation and preservation. Programmable organic semiconductor frameworks spatially organize oxidative flux and intermediate residence, separating reaction zones from product domains to synchronize activation strength with stabilization and establish a selective oxidation ...
Minxian Zhang, Jie He, Jinqiang Zhang, Hongqi Sun, Shaobin Wang, Xiaoguang Duan   +5 more
wiley   +1 more source

Reprogramming the Immunosuppressive Microenvironment in Triple‐Negative Breast Cancer via FAP‐Targeted Nanoprobes for Multimodal Imaging and Photothermal Therapy

Advanced Materials, EarlyView.
Targeting cancer‐associated fibroblasts (CAFs) with fibroblast activation protein (FAP)‐directed nanoprobes for multimodal imaging and photothermal remodeling of the immunosuppressive microenvironment to enhance immunotherapy in triple‐negative breast cancer (TNBC).
Ling Zhan, Yanhong Chen, Jingjing Hu, Chunting Wang, Huanhuan Liu, Defan Yao, Dengbin Wang   +6 more
wiley   +1 more source

RegCGAN: Resampling with Regularized CGAN for Imbalanced Big Data Problem

Axioms
We consider the imbalanced data problem involving a new class of resampling-based models for classification. These models are variants of the conditional generative adversarial networks.
Liwen Xu, Ximeng Wang
doaj   +1 more source

Bioinspired Adaptive Surfaces for Intelligent Liquid Manipulation: Progressing From Passive and Active to Hybrid Strategies

Advanced Materials, EarlyView.
This review examines passive, active, and hybrid liquid manipulation strategies, highlighting hybrid approaches as an emerging route to reconcile energy efficiency with adaptive control. By actively reconstructing passive surfaces to store programmable interfacial energy, hybrid systems enable flexible yet low‐power liquid transport, with perspectives ...
Jiaqi Miao, Yiyuan Zhang, Liqiu Wang, Alan C. H. Tsang   +3 more
wiley   +1 more source

Hydrophobic MFI‐Type Zeolites via Alkali‐Cation‐Induced Defect Healing: Implications for Adsorbent and Catalyst Design

Advanced Materials, EarlyView.
Sub‐stoichiometric amounts of Na+ or K+ enhance defect healing during Silicalite‐1 (MFI) and TS‐1 calcination by promoting Si–O–Si annealing and healing framework vacancies. The resulting defect‐free zeolites are more hydrophobic and show improved butanol/water separation and improved activity and selectivity in the epoxidation of 1‐hexene, offering a ...
Christos Kanteler, Pau Ferri, Francisco Javier Escobar‐Bedia, Álvaro Mayoral, Alejandro Vidal‐Moya, Richard Kendra, Chen Lei, Miguel Palomino, Fernando Rey, Lukáš Grajciar, Christopher James Heard, Pedro Serna, Mercedes Boronat, Cristina Martínez, Manuel Moliner   +14 more
wiley   +1 more source

Data‐Driven Materials Science for Energy‐Sustainable Applications

Advanced Materials, EarlyView.
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley   +1 more source

Data Augmentation with Variational Autoencoder for Imbalanced Dataset

Learning from an imbalanced distribution presents a major challenge in predictive modeling, as it generally leads to a reduction in the performance of standard algorithms. Various approaches exist to address this issue, but many of them concern classification problems, with a limited focus on regression. In this paper, we introduce a novel method aimed
Samuel Stocksieker, Denys Pommeret, Arthur Charpentier   +2 more
openaire   +2 more sources

Noise‐Tunable Memristor Enabling Programmable Probabilistic Neurons for Frequency‐Selective Time‐Series Signal Encoding

Advanced Materials, EarlyView.
Memristors offer tunable resistance and intrinsic instability, making them promising tunable noise sources. We propose a spiking‐rate‐programmable probabilistic neuron using a Ru/TaOx/Pt memristor, where resistance‐dependent noise enables frequency‐selective encoding.
Do Hoon Kim, Seoeun Jang, Hakseung Rhee, Min Gu Lee, Daehee Kim, Taewook Go, Woon Hyung Cheong, Hanchan Song, Kyung Min Kim   +8 more
wiley   +1 more source

Fault diagnosis methods for imbalanced samples of hydraulic pumps based on DA-DCGAN

Scientific Reports
Status monitoring and fault diagnosis of mechanical equipment are vital for ensuring operational safety. However, real-world diagnostic scenarios often suffer from limited and imbalanced fault data, affecting model accuracy and reliability.
Yang Zhao, Anqi Jiang, Wanlu Jiang, Peiyao Zhang, Peng Xiong   +4 more
doaj   +1 more source