Results 221 to 230 of about 9,181,016 (294)
Label-free 3D computational imaging of spermatozoon locomotion, head spin and flagellum beating over a large volume. [PDF]
Daloglu MU +10 more
europepmc +1 more source
Reevaluating the Activity of ZIF‐8 Based FeNCs for Electrochemical Ammonia Production
Though receiving much attention, the field of electrochemical nitrogen reduction reaction (eNRR) to ammonia is marked by doubts about whether this reaction is possible in aqueous media. This work sheds light on this question for iron single‐atom on N‐doped carbon (FeNC) catalysts—a class of well‐known catalysts that is also worth testing for the sister
Caroline Schneider +6 more
wiley +1 more source
Computational imaging reveals shape differences between normal and malignant prostates on MRI. [PDF]
Rusu M +17 more
europepmc +1 more source
A solvent‐free mechanochemistry‐enabled supramolecular engineering strategy is developed to directly synthesize covalent‐interconnected two‐dimensional atomic‐layered carbon nitride nanosheets photocatalyst, bypassing conventional top‐down exfoliation requirements.
Fanglei Yao +7 more
wiley +1 more source
A frequency‐tunable ferroelectric synaptic transistor based on a buried‐gate InGaZnO channel and Al2O3/HfO2 dielectric stack exhibits linear and reversible weight updates using single‐polarity pulses. By switching between ferroelectric and trap‐assisted modes depending on input frequency, the device simplifies neuromorphic circuit design and achieves ...
Ojun Kwon +8 more
wiley +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
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
A hybrid anode composed of Cl‐functionalized curved nanographene and graphite enables ultra‐fast charging and long cycle life through an engineered morphology and sequential Li+ insertion. It delivers 100 mAh g−1 at 5 C with 70% capacity retention after 1000 cycles and maintains stable performance over 2000 cycles in pouch cells, providing a practical ...
Hyunji Cha +8 more
wiley +1 more source
Covalent Organic Frameworks for Water Sorption: The Importance of Framework Physical Stability
This study explores the water‐vapor stability of 2D covalent organic frameworks (COFs) with varying pore sizes. Results reveal microporous COFs demonstrate superior stability compared to mesoporous ones, despite lower water uptake. Mesoporous keto‐enamine‐linked COFs show enhanced stability due to intralayer hydrogen bonds, confirmed by simulations and
Wei Zhao +13 more
wiley +1 more source

