Results 131 to 140 of about 321,627 (335)
Advanced Functional Materials, EarlyView.This study investigates H4TBAPy‐based metal–organic frameworks (MOFs) ‐ NU‐1000, NU‐901, SrTBAPy, and BaTBAPy ‐ for multiphoton absorption (MPA) performance. It observes topology‐dependent variations in the 2PA cross‐section, with BaTBAPy exhibiting the highest activity.
Simon N. Deger +10 more
wiley +1 more source
Photoswitching Conduction in Framework Materials
Advanced Functional Materials, EarlyView.This mini‐review summarizes recent advances in state‐of‐the‐art proton and electron conduction in framework materials that can be remotely and reversibly switched on and off by light. It discusses the various photoswitching conduction mechanisms and the strategies employed to enhance photoswitched conductivity.
Helmy Pacheco Hernandez +4 more
wiley +1 more source
The Analyze Comparative of Physics Computational Thinking Skill (CTs) in Experiment Laboratory
Qubahan Academic JournalObjective: This study aimed to analyze students' response to the use of computational thinking from the perspective of computational tools and to analyze the influence of gender on students' computational thinking skills. Method: Research design using a
Suritno Fayanto +4 more
doaj +1 more source
Characterising computational thinking in mathematics education: a literature-informed Delphi study
, 2021 Maria Kallia +4 more
openalex +1 more source
Computational Thinking: A Disciplinary Perspective [PDF]
, 2021 Peter J. Denning, Matti Tedre
openalex +1 more source
MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance
Advanced Functional Materials, EarlyView.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
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
Advanced Functional Materials, EarlyView.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
In Between Code and Knowledge Exploring Students' Computational Thinking in Analyzing Arabic Texts
AsalibunaComputational thinking has become a crucial skill in the 21st century, particularly in fostering critical thinking and problem-solving abilities. In their research, the Arabic Language teacher for Grade X Religion 1 at MAN 2 Banyuwangi has employed ...
Ahmad Faisal Zam Ani +4 more
doaj +1 more source
The Implementation of Computational Thinking on Mathematics Learning Research: A Systematic Literature Review [PDF]
, 2023 Ahmad Mukhibin, Dadang Juandi
openalex +1 more source