Results 211 to 220 of about 1,939,164 (288)

Investigation of Resonance Characteristics of More Than 10 000 Metal‐Coated Silicon MEMS Cantilevers Using Machine Learning

Advanced Engineering Materials, EarlyView.
More than 10 000 metal‐coated silicon MEMS cantilevers are fabricated and characterized to build a large‐scale experimental dataset spanning multiple vibrational modes. Machine learning algorithms are benchmarked to predict resonance frequency and quality factor, with ensemble based models achieving accuracy approaching experimental uncertainty.
Sina Zare Pakzad, Saurabh Thorat, Andre Loch Gesing, Dominik Huber, Christopher Zellner, Patrick Egger, Georg Pfusterschmied, Ulrich Schmid, Michael Schneider   +8 more
wiley   +1 more source

Optimisation of the gelation process and performance characterisation of nitrogen-containing Guanylurea double-based explosive materials through rheological modelling and parameter coupling analysis. [PDF]

RSC Adv
Dong J, Dong J, Mao C, Duan Y, He X, Ji W.   +5 more
europepmc   +1 more source

Influence of Fe Particle Size Distribution on Chemical Homogeneity, Microstructure, and Crack Formation in Fe–SiC Powder Blends Processed by PBF‐LB/M

Advanced Engineering Materials, EarlyView.
The influence of Fe particle size on in situ alloying of Fe–SiC powder blends in PBF‐LB/M is revealed. Contrary to expectations, the coarser Fe fraction provides a broader crack‐free processing window and slightly improved elemental homogeneity while producing higher but more variable hardness. The results highlight a complex trade‐off between particle
Anna Luise Strauch, Anastasiya Toenjes, Matthias Steinbacher   +2 more
wiley   +1 more source

Digital twin optimization of water supply pump stations considering energy use, water hammer, and lifespan. [PDF]

Sci Rep
Liu Y, Cheng L, Liu K, Zhou T.
europepmc   +1 more source

Effect of Calendering and Surface Treatment on the Thermochromic Response of Cholesteric Liquid Crystals on PET Nonwovens

Advanced Engineering Materials, EarlyView.
This study explores the influences of calendering and surface treatment during direct ink writing (DIW) of thermochromic cholesteric liquid crystal (CLC) on PET nonwovens. For the PVA‐coated nonwovens, calendering reduces pore size leading to reduced ink absorption and enhanced spreading. The NeverWet‐coated nonwovens improve thermochromic responses by
Sreenivasan Sreenivasan Narayanan, Lineth Pérez Monsalve, Christina Tang, Hong Zhao   +3 more
wiley   +1 more source

Machine-learning-assisted continuous flow synthesis of clonidine. [PDF]

Commun Chem
Sagandira CR, Nqeketo S, Pomberger A, Wigh D, Len C.   +4 more
europepmc   +1 more source

Enhancing Low‐Temperature Performance of Sodium‐Ion Batteries via Anion‐Solvent Interactions

Advanced Functional Materials, EarlyView.
DOL is introduced into electrolytes as a co‐solvent, increasing slat solubility, ion conductivity, and the de‐solvent process, and forming an anion‐rich solvent shell due to its high interaction with anion. With the above virtues, the batteries using this electrolyte exhibit excellent cycling stability at low temperatures. Abstract Sodium‐ion batteries
Cheng Zheng, Qian Yao, Yanan Sun, Hongyu Lv, Zhongchao Bai, Guoliang Zhang, Nana Wang, Jian Yang   +7 more
wiley   +1 more source

FFRLS-MPC: An adaptive model predictive control method for robust ship course keeping. [PDF]

Sci Rep
Huang Y, Liu J, Huang J.
europepmc   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

MemAF-KTCBM: a Memory-Aware Fractional optimisation-enabled deep learning model for atherosclerosis classification. [PDF]

Front Med Technol
Pravalika N, A J, Rajamani V.
europepmc   +1 more source