Correction: Optimizing electric vehicle energy consumption prediction through machine learning and ensemble approaches. [PDF]
Hussain I +5 more
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
Triplet Excitons Unlock Electroluminescence from Insulating Lanthanide Nanocrystals for Light-Emitting Diode Applications. [PDF]
Li W, Lian W, Tu D.
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
High-efficiency, polarization-independent broadband metasurface absorber with angular stability for ISM applications. [PDF]
Amer AAG, Shamsan ZA, Algamili AS.
europepmc +1 more source
Organizing Committee: Advances in Electrical and Electronic Engineering: From Theory to Applications (Series 2): Proceedings of the International Conference of Electrical and Electronic Engineering (ICon3E 2019) [PDF]
openalex +1 more source

