Biomass Native Structure Into Functional Carbon‐Based Catalysts for Fenton‐Like Reactions
This study indicates that eight biomasses with 2D flaky and 1D acicular structures influence surface O types, morphology, defects, N doping, sp2 C, and Co nanoparticles loading in three series of carbon, N‐doped carbon, and cobalt/graphitic carbon. This work identifies how these structural factors impact catalytic pathways, enhancing selective electron
Wenjie Tian +7 more
wiley +1 more source
Electroactive Metal–Organic Frameworks for Electrocatalysis
Electrocatalysis is crucial in sustainable energy conversion as it enables efficient chemical transformations. The review discusses how metal–organic frameworks can revolutionize this field by offering tailorable structures and active site tunability, enabling efficient and selective electrocatalytic processes.
Irena Senkovska +7 more
wiley +1 more source
Condition-fusion-and-hiding denoising diffusion model for electrocardiogram lead reconstruction. [PDF]
Wei X +6 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
Initiating a Life Skills Module to Prevent Drug Abuse Among Indonesian Adolescents Using Social Cognitive Theory. [PDF]
Utami YC +4 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
Dual-temporal inflow-outflow dependency modeling for short-term metro outflow prediction. [PDF]
Hu W, Huang Z, Cai J, Zhao X.
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
CancerSubtypeXplore: A Modular Platform for Multiomics Cancer Subtype Prediction and Biomarker Consensus Discovery. [PDF]
Jin D, Bian B, Saito Y.
europepmc +1 more source
This review systematically highlights the latest achievements in mixed‐valence states relevant to hydrogen and oxygen evolution reactions, providing essential insights into future directions and methods for large‐scale practical implementation. This critical review is expected to provide an overview of recent advancements in diverse valence‐state metal
Jitendra N. Tiwari +4 more
wiley +1 more source

