Results 121 to 130 of about 48,907 (262)

Direct Metal Deposition of Graphene–Ti28Nb35.4Zr Matrix Composites With Enhanced Mechanical, Corrosion, and Biocompatibility Properties for Bone Implants

Advanced Engineering Materials, EarlyView.
Graphene nanoplatelet (0.1 wt.%) reinforcement significantly enhances the performance of β Ti‐28Nb‐35.4Zr alloy. Grain refinement, reduced water contact angle, and improved surface characteristics promote osteoblast adhesion and complete surface coverage after 7 days.
Khurram Munir, Jixing Lin, Yuncang Li, Li Zhu, Paul F. A. Wright, Cuie Wen   +5 more
wiley   +1 more source

Cathodic Cage Plasma Deposition of Nanostructured Cu–Fe–Se Coatings on Poly(methyl Methacrylate)

Advanced Engineering Materials, EarlyView.
Nanostructured Cu–Fe–Se coatings are deposited on PMMA by a modified cathodic cage plasma process, enabling low‐temperature deposition on polymer substrates. A transition from discontinuous to compact morphology is observed with temperature, with optimal properties at 200°C, where improved CuFeSe2‐type bonding, lowest sheet resistance, and favorable ...
V. S. S. Sobrinho, M. Naeem, T. H. C. Costa, M. S. Libório, J. C. A. Queiroz, C. B. B. Luna, R. R. M. Sousa, P. S. Vieira, E. M. Araújo   +8 more
wiley   +1 more source

An Experimental High‐Throughput Approach for the Screening of Hard Magnet Materials

Advanced Engineering Materials, EarlyView.
An entire workflow for the high‐throughput characterization and analysis of compositionally graded magnetic films is presented. Characterization protocols, data management tools and data analysis approaches are illustrated with test case Sm(Fe, V)12 based films.
William Rigaut, Pierre Le Berre, Hamdi Jaballah, Lukas Fink, Victor Poline, Richard Haettel, Stéphane Grenier, Gilbert Chahine, Ewen Bellec, Guillaume Buatier, Wilfried Hortschitz, Santa Pile, Thomas Schrefl, Nils Blanc, Yuan Hong, Thibaut Devillers, Nora M. Dempsey   +16 more
wiley   +1 more source

In response to stress: quicker, yet bigger. [PDF]

Blood Adv
Palis J.
europepmc   +1 more source

In Situ Constructed Magnetic Core‐Shell Hydrogen‐Bonded Organic Framework‐on‐Metal–Organic Framework Structure: an Efficient Catalyst for Peroxymonosulfate Activation

Advanced Functional Materials, EarlyView.
In this work, a magnetic core‐shell catalyst (HOF‐on‐Fe3O4/ZIF‐67) is successfully synthesized, consisting of a metal–organic framework (ZIF‐67) with magnetic Fe3O4 as the core and a porous hydrogen‐bonded organic framework (HOF) as the shell. The catalyst efficiently activated peroxymonosulfate, resulting in rapid and effective removal of water ...
Yingying Du, Chenhui Ding, Chao Deng, Susanta Banerjee, Seema Agarwal   +4 more
wiley   +1 more source

Understanding and Optimizing Li Substitution in P2‐Type Sodium Layered Oxides for Sodium‐Ion Batteries

Advanced Functional Materials, EarlyView.
This work explores Li‐substituted P2 layered oxides for Na‐ion batteries by crystallographic and electrochemical studies. The effect of lithium on superstructure orderings, on phase transitions during synthesis and electrochemical cycling and on the interplay of O‐ versus TM‐redox is revealed via various advanced techniques, including semi‐simultaneous 
Mingfeng Xu, Giovanni Gammaitoni, Michael Häfner, Eduardo Villalobos‐Portillo, Carlo Marini, Matteo Bianchini   +5 more
wiley   +1 more source

Acute cardiac dysfunction and rapid descending aortic expansion following surgery for acute Stanford type A aortic dissection: a case report. [PDF]

Eur Heart J Case Rep
Yokawa K, Nakagawa T, Tanaka Y, Yoshida K, Wakiyama H.   +4 more
europepmc   +1 more source

Stretching the Printability Metric in Direct‐Ink Writing with Highly Extensible Yield‐Stress Fluids

Advanced Functional Materials, EarlyView.
This study introduces “drawability” as a new metric for assessing printability in direct‐ink writing, focusing on gap‐spanning performance and speed robustness. By designing yield‐stress fluids with high extensibility, we demonstrate that extensional strain‐to‐break significantly enhances printability.
Chaimongkol Saengow, Samya Sen, Joaquin Yus, Eliza E. Lovrich, Amanda G. Hoika, Kelly M. Chang, Arielle A. Pfeil, Nellie Haug, Amy J. Wagoner Johnson, Randy H. Ewoldt   +9 more
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, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source