Results 211 to 220 of about 1,092,040 (293)

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

A molecular framework for the GS2-SUG1 module-mediated control of grain size and weight in rice. [PDF]

open access: yesNat Commun
Li Y   +11 more
europepmc   +1 more source

Understanding and Tuning Mobile Interfaces in Ferroelectric Hf0.5Zr0.5O2 Thin Films in Relation to Microstructure

open access: yesAdvanced Functional Materials, EarlyView.
Ferroelectricity in thin HfO2‐based films offers great possibilities for next‐generation neuromorphic memory devices. There, the response to subcoercive voltage signals is driven by the movement of mobile interfaces and their interaction with crystal defects – a yet rather unexplored aspect, which we shed light on and gain new insights into the complex
Maximilian T. Becker   +11 more
wiley   +1 more source

Ceramic Particle‐Reinforced Medium‐Entropy Alloys With Outstanding Mechanical Properties Prepared by Novel Micro‐LPBF

open access: yesAdvanced Functional Materials, EarlyView.
An innovative medium entropy alloy (MEA) composite material was fabricated via micro laser powder bed fusion (μ‐LPBF) with appropriate nano‐ceramic particles doping and exhibited markedly improved overall performance, including synergistically enhanced strength and ductility, increased hardness and compressive strength, improved wear resistance and ...
Zhonglin Shen, Mingwang Fu
wiley   +1 more source

Predicting Atomic Charges in MOFs by Topological Charge Equilibration

open access: yesAdvanced Functional Materials, EarlyView.
An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi   +2 more
wiley   +1 more source

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