Results 81 to 90 of about 637,067 (262)

Stochastically Generated Digital Twins of 3D Solid‐State Electrolyte Architecture

open access: yesAdvanced Functional Materials, EarlyView.
Digital Twins of random porous tape‐cast solid‐state battery architectures across µm to mm feature sizes from FIB‐SEM to X‐Ray µCT, respectively. Abstract Solid‐state lithium batteries (SSBs) have the potential to overcome conventional Li‐ion batteries in performance and safety.
Jonathan O'Neill   +3 more
wiley   +1 more source

Self‐Assembled Heterosymmetric Structure with Tunable Polarization Optics for Reversible Matrix Encryption

open access: yesAdvanced Functional Materials, EarlyView.
Sustainable films with heterosymmetric structures, harmoniously integrating symmetry and asymmetry, are fabricated using cellulose nanocrystals and hydrophilic nanolignin via evaporation‐induced self‐assembly, which exhibit excellent multiple polarization optical properties.
Qun Song   +7 more
wiley   +1 more source

Gaussian‐Sigmoid Reinforcement Transistors: Resolving Exploration‐Exploitation Trade‐Off Through Gate Voltage‐Controlled Activation Functions

open access: yesAdvanced Functional Materials, EarlyView.
The characteristics of a vertical n–p–i–p heterostructure transistor device, which exhibits a voltage‐tunable transition between Gaussian and sigmoid functions, are investigated. The mixed state of the transfer curve enables the utilization of both exploitation and exploration, improving computational performance in reinforcement learning tasks ...
Jisoo Park   +7 more
wiley   +1 more source

Locking Metastable Topological Domains in Nematic Liquid Crystal Pi Cells

open access: yesAdvanced Functional Materials, EarlyView.
Selective photopolymerization in the presence of a controlled voltage defines permanent director walls that lock‐in metastable bend and twist configurations within nematic liquid crystal Pi cells. Q‐tensor simulations corroborate the experiments, demonstrating the topological state stabilization.
Adithya Pradeep   +7 more
wiley   +1 more source

SMaRT Stacking: A Methodology to Produce Optimally Layered EMI Shields with Maximal Green Index Using Fused Deposition Modeling

open access: yesAdvanced Functional Materials, EarlyView.
Electromagnetic interference (EMI) shields consisting of polylactic acid (PLA) in layers with different concentrations of multiwalled carbon nanotubes (MWCNT) are produced using additive manufacturing. The permittivity function of layers with different filler concentrations is learned using data of homogeneous and randomly ordered shields.
Stijn De Smedt   +5 more
wiley   +1 more source

An Ultra‐Robust Memristor Based on Vertically Aligned Nanocomposite with Highly Defective Vertical Channels for Neuromorphic Computing

open access: yesAdvanced Functional Materials, EarlyView.
An ultra‐robust memristor based on SrTiO3‐CeO2 (S‐C) vertically aligned nanocomposite (VAN) achieving exceptional endurance of 1012 switching cycles via interface engineering. Artificial neural networks (ANNs) integrated with S‐C VAN memristors exhibit high training accuracy across multiple datasets.
Zedong Hu   +12 more
wiley   +1 more source

Design and Applications of Multi‐Frequency Programmable Metamaterials for Adaptive Stealth

open access: yesAdvanced Functional Materials, EarlyView.
This article provides a comprehensive overview of metamaterials, including their fundamental principles, properties, synthesis techniques, and applications in stealth, as well as their challenges and future prospects. It covers topics that are more advanced than those typically discussed in existing review articles, while still being closely connected ...
Jonathan Tersur Orasugh   +4 more
wiley   +1 more source

Amorphous High Entropy Alloy Nanosheets Enabling Robust Li–S Batteries

open access: yesAdvanced Functional Materials, EarlyView.
Amorphous ultrathin FeCoNiMoW high entropy alloy nanosheets are incorporated into the polypropylene separator of lithium‐sulfur batteries, enhancing their capacity, rate performance, and cycling stability. Abstract High‐entropy alloys (HEAs) show great potential for catalyzing complex multi‐step reactions, but optimizing their parameters, i.e ...
Ren He   +20 more
wiley   +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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