Results 191 to 200 of about 8,537,021 (379)

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

A Dynamic Distribution Method Composed of Mathematical Programming and Heuristic Method and Its Application to Water Management

, 1994
Hiromitsu Kurisu, T. Nishiya, Nihei Tachi, Hiromu ADACHI   +3 more
openalex   +2 more sources

A Mathematical Study to Select Fractionation Regimen Based on Physical Dose Distribution and the Linear–Quadratic Model [PDF]

, 2012
Masahiro Mizuta, Seishin Takao, Hiroyuki Date, Naoki Kishimoto, Kenneth Sutherland, Rikiya Onimaru, Hiroki Shirato   +6 more
openalex   +1 more source

Distributed mathematical problem solving

, 1995
Calmet, Jacques, Homann, Karsten
openaire   +3 more sources

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

Using the log-normal distribution in analyzing aerosols: The mathematical reasoning underlying the various diameters used and the plotting procedure

, 1993
M. Tobias
openalex   +2 more sources

Mathematical modeling and comparison of protein size distribution in different plant, animal, fungal and microbial species reveals a negative correlation between protein size and protein number, thus providing insight into the evolution of proteomes [PDF]

, 2012
Axel Tiessen, Paulino Pérez‐Rodríguez, Luis Delaye   +2 more
openalex   +1 more source

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

A systematic literature review on analytical thinking development in mathematics education: trends across time and countries. [PDF]

Front Psychol
Wang M, Mohd Matore MEE, Rosli R.
europepmc   +1 more source

MATHEMATICAL MODEL FOR UNSTEADY STATE HEAT ANALYSIS OF A LARGE SPACE, INCLUDING THE PREDICTION OF VERTICAL AIR TEMPERATURE DISTRIBUTION : Study on a thermal environment design system for large spaces Part 2

, 1992
Satoshi Togari, Yoshinobu Arai, Katsuhiro Miura   +2 more
openalex   +2 more sources