Results 231 to 240 of about 487,374 (296)
Developing Biodegradable Films from Mango (<i>Mangifera indica</i>) Starch and Extract: A Rheological and Physical Study. [PDF]
Lastra-Ripoll SE +5 more
europepmc +1 more source
Reduced Variability in Threshold Switches Using Heterostructures of SiOx and Vertically Aligned MoS2
Heterostructures of SiOx and vertically aligned MoS2 exhibit reliable threshold switching by guiding Ag ion migration through van der Waals gaps. Compared to SiOx‐only devices, these heterostructures demonstrate higher switching voltages, faster switching speeds, and reduced variability.
Jimin Lee +9 more
wiley +1 more source
Optimal Design of Electromagnetic Absorber Based on Magnetic Field Directional Consistency. [PDF]
Wang J +6 more
europepmc +1 more source
Pressure‐Induced Structural and Magnetic Evolution in Layered Antiferromagnet YbMn2Sb2
Pressure tunes the delicate balance between structure, magnetism, and electronic states in quantum materials. In YbMn2Sb2, high‐pressure X‐ray and neutron diffraction reveal a trigonal‐to‐monoclinic transition near 3.5 GPa, accompanied by unconventional magnetic ordering.
Mingyu Xu +9 more
wiley +1 more source
ABSTRACT Understanding how policy instruments with overlapping goals interact is crucial for leveraging their synergies. This study explores the mechanisms for regional nature parks (a form of protected areas that impose no restrictions on agriculture) to enhance the adoption of biodiversity‐conserving agri‐environment schemes (AES) in Switzerland ...
Yanbing Wang +3 more
wiley +1 more source
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Massart iron oxide nanoparticles in mechanobiology. [PDF]
Reffay M, Tessier G, Berret JF.
europepmc +1 more source
Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley +1 more source

