Results 141 to 150 of about 26,242 (276)
The dielectric properties of clays are studied on the level of individual monolayers and functional double stacks. The material breakdown characteristics and charge storage performance are analyzed. For illustration, a defined charge pattern representing a cuneiform character is produced, written into a microscopic clay tile, referencing the origins of
Sebastian Gödrich +6 more
wiley +1 more source
crystIT: complexity and configurational entropy of crystal structures via information theory. [PDF]
Kaußler C, Kieslich G.
europepmc +1 more source
A previously unreported coordination motif stabilising single Fe atoms by indigo chelation and pyridyl coordination on Au(111) has been revealed. By using planar tritopic pyridyl linkers (TPyB), extended 2D porous networks of indigo3(TPyB)2Fe6 form. These networks can be crystalline or vitreous and offer an environment where individual coordination ...
Hongxiang Xu +9 more
wiley +1 more source
Configurational Entropy of Folded Proteins and Its Importance for Intrinsically Disordered Proteins. [PDF]
Liu M +7 more
europepmc +1 more source
Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz +3 more
wiley +1 more source
Improvement of critical current density of REBa2Cu3O7-δ by increase in configurational entropy of mixing. [PDF]
Yamashita A, Shukunami Y, Mizuguchi Y.
europepmc +1 more source
MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance
Metal‐organic frameworks (MOFs) and covalent organic frameworks (COFs) hold promise for advanced electronics. However, discrepancies in reported electrical conductivities highlight the importance of measurement methodologies. This review explores intrinsic charge transport mechanisms and extrinsic factors influencing performance, and critically ...
Jonas F. Pöhls, R. Thomas Weitz
wiley +1 more source
Configurational Entropy Driven High-Pressure Behaviour of a Flexible Metal-Organic Framework (MOF). [PDF]
Vervoorts P +7 more
europepmc +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Is configurational entropy the main stabilizing term in rock-salt Mg0.2Co0.2Ni0.2Cu0.2Zn0.2O high entropy oxide? [PDF]
Fracchia M +4 more
europepmc +1 more source

