Results 141 to 150 of about 7,625,262 (337)

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

Advanced 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, Hongyi Dou, Jeremy B. Gan, Cun Li, Xuanyu Sheng, Juanjuan Lu, Abhijeet Choudhury, Jialong Huang, Yizhi Zhang, Zhongxia Shang, Ye Cao, Xinghang Zhang, Haiyan Wang   +12 more
wiley   +1 more source

Kidney compartment model. [Mathematical model for iodohippurate distribution as a function of time]

, 1976
G.T. Gullberg
openalex   +2 more sources

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

Advanced 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, Ankita Mohanty, Amit Malakar, Suryasarathi Bose, Suprakas Sinha Ray   +4 more
wiley   +1 more source

Amorphous High Entropy Alloy Nanosheets Enabling Robust Li–S Batteries

Advanced 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, Seungho Lee, Yang Ding, Chen Huang, Xuan Lu, Lirong Zheng, Ao Yu, Chaoyue Zhang, Canhuang Li, Xiaoyu Bi, Yaqiang Li, Yaqi Liao, Junshan Li, Ahmad Ostovari Moghaddam, Salimov Yernar, Ying Xu, Maria Ibáñez, Chaoqi Zhang, Linlin Yang, Yingtang Zhou, Andreu Cabot   +20 more
wiley   +1 more source

Equations for a potential algebraic approach to the twin prime conjecture. Addendum to: "On the numbers that determine the distribution of twin primes" [PDF]

Surveys in Mathematics and its Applications
This is an Addendum to: Article: On the numbers that determine the distribution of twin primes Author: Antonie Dinculescu Published in: Surveys in Mathematics and its Applications, 13 (2018), 171–181. Full text:
Antonie Dinculescu
doaj  

A mathematical model for the prediction of granule size distribution for multicomponent sinter feed.

, 1989
Allan Waters, James D. Litster, S.K. Nicol   +2 more
openalex   +1 more source

Mathematical modeling of harmonic-timbre structure with multi-beta-distribution [PDF]

, 2009
Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki   +2 more
openalex   +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

A Mathematical Model of Blast Furnace with Radial Distribution of Gas Flow, Heat Transfer and Reactions Considered

, 1982
Michiharu Hatano, Koichi Kurita
openalex   +2 more sources

Electron Compensation Enhanced Triboelectric Sensor Assisted by Machine Learning for Tactile Perception Recognition

Advanced Functional Materials, EarlyView.
Integrating polyethyleneimine and carbon black into polyurethane enhances electron transport and mechanical durability. The resulting sensor achieves significantly improved electrical signal and sensitivity, enabling efficient machine learning‐based tactile signal recognition in bionic applications.
Xiangkun Bo, Wei Wang, Hong Zhao, Ruiqin Zhang, Walid A. Daoud   +4 more
wiley   +1 more source