Results 101 to 110 of about 5,337 (224)
Bio‐Based Polyurethanes for Sustainable and Multifunctional Applications
Bio‐based polyurethanes prepared from vegetable oils, lignin, and polysaccharides have attracted increasing interest as alternatives to fossil‐derived polyurethanes. This review summarizes recent progress in their chemistry, structural engineering, and advanced applications, highlighting the roles of feedstocks, chain‐segment design, dynamic covalent ...
Xin Li +6 more
wiley +1 more source
In this study, MPDA NPs were engineered to encapsulate CTT. To further increase renal accumulation of CTT, L‐serine was conjugated to the surface of the MPDA nanoparticles (CTT/MPDA@L‐Ser NPs). CTT/MPDA@L‐Ser NPs inhibit DPEP1 activity, thereby restoring ferroptosis defense mechanisms through upregulation of GPX4 and SLC7A11 expression, ultimately ...
Wanbing Qin +12 more
wiley +1 more source
Learning Work Function via Implicit Reasoning on Electrostatic Potential Landscapes
StructPot‐CLR establishes a cross‐modal contrastive learning framework that aligns the crystal structures of 2D materials with plane‐averaged electrostatic potential landscapes for physically informed work‐function prediction. The model achieves an MAE of 0.265 eV and an R2 of 0.902 on the held‐out test set while accurately preserving key morphological
Haoyu Wan, Yue Wu, Tianhao Su, Deng Pan
wiley +1 more source
An Intravesical Akkermansia muciniphila‐Based Chemo‐Immunotherapeutic Platform for Bladder Cancer
Pasteurized Akkermansia muciniphila is engineered into an intravesical F127/doxorubicin platform that couples localized chemotherapy with immune remodeling. By inducing apoptosis, ferroptosis, and immunogenic cell death, this chemo‐immunotherapeutic system enhances dendritic‐cell maturation, antigen cross‐presentation, and tumor‐specific CD8+ T‐cell ...
Rongkang Li +11 more
wiley +1 more source
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen +4 more
wiley +1 more source
Deciphering Intricacies in Directional CO2 Conversion From Electrolysis to CO2 Batteries
This review will delve into the inherent connections and distinctions of CO2‐directed conversion in ECO2RR and CO2 batteries, in terms of product types, catalyst selection, catalytic mechanisms, and electrochemical performances, while proposing a benchmarking framework for the evaluation of CO2 batteries and innovative CO2 battery configurations for ...
Changfan Xu +5 more
wiley +1 more source
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park +19 more
wiley +1 more source
Low Participation and Risk Reduction Potential of Supplemental Crop Insurance in the United States
ABSTRACT Federally subsidized crop insurance is a cornerstone of U.S. farm risk management, yet policies with the greatest share of participation only trigger indemnities after losses exceed 15%. Supplemental insurance was introduced to cover part of this deductible, but participation remains largely unchanged.
Francis Tsiboe +2 more
wiley +1 more source
ABSTRACT This study investigates how consumer taste and brand equity perceptions shape the acceptance of plant‐based milk products. Using a blind/informed tasting experiment, we evaluated consumers' willingness to buy (WTB) and taste perception of a plant‐based milk alternative produced by a traditional dairy brand, compared with competing plant‐based ...
Federico Parmiggiani +6 more
wiley +1 more source
Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang +4 more
wiley +1 more source

