Results 121 to 130 of about 406,303 (299)

3D (Bio) Printing Combined Fiber Fabrication Methods for Tissue Engineering Applications: Possibilities and Limitations

open access: yesAdvanced Functional Materials, EarlyView.
Biofabrication aims at providing innovative technologies and tools for the fabrication of tissue‐like constructs for tissue engineering and regenerative medicine applications. By integrating multiple biofabrication technologies, such as 3D (bio) printing with fiber fabrication methods, it would be more realistic to reconstruct native tissue's ...
Waseem Kitana   +2 more
wiley   +1 more source

Investigation of the impact of rotor shaping on the torque and radial force harmonics of a V‐shape interior permanent magnet synchronous machine

open access: yesIET Electric Power Applications
This paper introduces a technique aimed at improving the performance of an interior permanent magnet synchronous machine (IPMSM) by reducing torque ripple and radial force harmonics.
Moien Masoumi   +4 more
doaj   +1 more source

Selective Benzene Capture by Metal‐Organic Frameworks

open access: yesAdvanced Functional Materials, EarlyView.
Metal‐organic frameworks (MOFs) hold significant potential for capturing benzene from air emissions and hydrocarbon mixtures in liquid phases. This capability stems from their precisely engineered structures, versatile chemistries, and diverse binding interactions.
Zongsu Han   +4 more
wiley   +1 more source

Laser‐Induced Graphene from Waste Almond Shells

open access: yesAdvanced Functional Materials, EarlyView.
Almond shells, an abundant agricultural by‐product, are repurposed to create a fully bioderived almond shell/chitosan composite (ASC) degradable in soil. ASC is converted into laser‐induced graphene (LIG) by laser scribing and proposed as a substrate for transient electronics.
Yulia Steksova   +9 more
wiley   +1 more source

Reinforcement Learning Optimization of Coaxial Magnetic Gear Geometry with Finite Element Analysis

open access: yesMachines
This manuscript presents a reinforcement learning (RL) agent method to optimize the geometry of a coaxial magnetic gear using a 2D finite element magnetic (FEM) simulation.
Georgi Ivanov   +5 more
doaj   +1 more source

Electroactive Metal–Organic Frameworks for Electrocatalysis

open access: yesAdvanced Functional Materials, EarlyView.
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

Smart, Bio‐Inspired Polymers and Bio‐Based Molecules Modified by Zwitterionic Motifs to Design Next‐Generation Materials for Medical Applications

open access: yesAdvanced Functional Materials, EarlyView.
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

Structure of software and hardware module for research of DC electrical machines. Part 1

open access: yesВесці Нацыянальнай акадэміі навук Беларусі: Серыя фізіка-тэхнічных навук
The structure of a hardware and software complex for the study of DC electric machines and a mathematical model of its electromechanical part taking into account the influence of temperature on the resistance of the armature winding have been developed ...
A. B. Menzhinsky   +3 more
doaj   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

open access: yesAdvanced 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

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