Results 271 to 280 of about 20,489,060 (330)
Bayesian optimization enabled the design of PA56 system with just 8 wt% additives, achieving limiting oxygen index 30.5%, tensile strength 80.9 MPa, and UL‐94 V‐0 rating. Without prior knowledge, the algorithm uncovered synergistic effects between aluminum diethyl‐phosphinate and nanoclay.
Burcu Ozdemir +4 more
wiley +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
Advanced Experiment Design Strategies for Drug Development
Wang et al. analyze 592 drug development studies published between 2020 and 2024 that applied design of experiments methodologies. The review surveys both classical and emerging approaches—including Bayesian optimization and active learning—and identifies a critical gap between advanced experimental strategies and their practical adoption in ...
Fanjin Wang +3 more
wiley +1 more source
A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley +1 more source
Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia +1 more
wiley +1 more source
We propose a residual‐based adversarial‐gradient moving sample (RAMS) method for scientific machine learning that treats samples as trainable variables and updates them to maximize the physics residual, thereby effectively concentrating samples in inadequately learned regions.
Weihang Ouyang +4 more
wiley +1 more source
Quercetin improves the protection of hydroxysafflor yellow a against cerebral ischemic injury by modulating of blood-brain barrier and src-p-gp-mmp-9 signalling. [PDF]
Li X +10 more
europepmc +1 more source
Hypoxia modulates P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP) drug transporters in brain endothelial cells of the developing human blood-brain barrier. [PDF]
Mughis H +4 more
europepmc +1 more source
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Flavonoids as P-gp inhibitors: a systematic review of SARs.
Current Medicinal Chemistry, 2019P-glycoprotein, also known as ABCB1 in the ABC transporter family, confers the simultaneous resistance of metastatic cancer cells towards various anticancer drugs with different targets and diverse chemical structures.
Jiahua Cui, Xiaoyang Liu, L. Chow
semanticscholar +3 more sources

