Results 181 to 190 of about 15,038,588 (334)
Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani +4 more
wiley +1 more source
Simplified technique of immuno-electrophoretic assay of human intrinsic factor on acrylamide gel. [PDF]
Karna Dev Bardhan +2 more
openalex +1 more source
The share of technical thermoplastics is expected to grow further in the e‐mobility segment. In this study, a detailed temperature‐based tribological characterization of technical thermoplastics is performed. The tribological properties are discussed in terms of the dynamic mechanical properties of polymers at different ambient temperatures. A proof of
Harsha Raghuram +2 more
wiley +1 more source
RFX4 is an intrinsic factor for neuronal differentiation through induction of proneural genes POU3F2 and NEUROD1. [PDF]
Choi W +9 more
europepmc +1 more source
What intrinsic factors influence responsiveness to acupuncture in pain?: a review of pre-clinical studies that used responder analysis [PDF]
Yu-Kang Kim +9 more
openalex +1 more source
Subgrain and Cavity Development during Creep of Al‐3.85%Mg
Al‐3.85%Mg does form subgrains if crept at very high strains. This fact allows the unification of the creep description in two different alloys such as pure Al and Al–Mg alloys. It is classically considered that the creep mechanisms for type M (e.g., pure Al) and type A alloys (e.g., Al–Mg alloys) are different.
Augusta Isaac +6 more
wiley +1 more source
Intrinsic factors ofPeltigeralichens influence the structure of the associated soil bacterial microbiota [PDF]
Diego Leiva +3 more
openalex +1 more source

