Results 71 to 80 of about 308,505 (215)

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

Advanced Engineering Materials, EarlyView.
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle, Cesar Alvarez‐Llamas, Vincent Motto‐Ros, Christophe Dujardin, Jérémie Margueritat, David Rodney   +5 more
wiley   +1 more source

Small signal stability analysis and frequency control in a single-area multi-source electrical energy system [PDF]

Hydrogen, Fuel Cell & Energy Storage
One of the important parameters in power system stability is frequency. The importance and difficulty of frequency control in a multi-area power system increases with the integration of several power generation sources.
Ghazanfar Shahgholian, Majid Dehghani, Mohammad Reza Yousefi, Sayyed Mohammad Mehdi Mirtalaei   +3 more
doaj   +1 more source

New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design

Advanced Engineering Materials, EarlyView.
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare, Y. Beideler, D. Chune, R. De Guio, T. Roland, H. Chibane   +5 more
wiley   +1 more source

Extrusion‐Based Additive Manufacturing of Advanced Ceramics: Strengthening Mechanisms and Process Optimization Review

Advanced Engineering Materials, EarlyView.
This review comprehensively evaluates extrusion‐based additive manufacturing for advanced ceramics, detailing feedstock options and key process parameters. By critically addressing defect mechanisms like porosity and cracking, the work highlights optimization strategies through machine learning and advanced postprocessing.
Meisam Bakhtiari, Mohammad Hadi Sheikh‐Ansari, Avinash Borgaonkar, Mehran Dadkhah, Abdollah Saboori   +4 more
wiley   +1 more source

The Influence of Field‐Assisted Sintering Technology (FAST) Temperature and Cooling Rate on the Microstructural Evolution in Gamma‐Titanium Aluminide Alloy GE4822

Advanced Engineering Materials, EarlyView.
Controlling the Field Assisted Sintering Technology (FAST) parameters, dwell temperature and cooling rate, significantly influences the microstructural evolution in titanium aluminide GE4822. Significant γ‐lamellar colonies develop only upon cooling through the α‐transus.
Jack Krohn, James Pepper, Martin Jackson
wiley   +1 more source

Two-stage optimization of hydrogen and storage coordination for a multi-region flexible intermodal multi-energy port system

Frontiers in Energy Research
To address the issue of imbalanced electricity and hydrogen supply and demand in the flexible multi-energy port area system, a multi-regional operational optimization and energy storage capacity allocation strategy considering the working status of ...
Yueyang Xu, Haijun Fu, Junru Yang, Leyuan Zhao, Yang Zhang   +4 more
doaj   +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

Laser‐Induced Graphene from Waste Almond Shells

Advanced Functional Materials, EarlyView.
Almond shells, an abundant agricultural by‐product, are repurposed to create a fully bioderived almond shell/chitosan composite (ASC) degradable in soil. ASC is converted into laser‐induced graphene (LIG) by laser scribing and proposed as a substrate for transient electronics.
Yulia Steksova, Anna Chiara Bressi, Marina Galliani, Attilio Marino, Gianni Ciofani, Eduardo Machado‐Charry, Hilda Gomez Bernal, Alessandra Francini, Luca Sebastiani, Francesco Greco   +9 more
wiley   +1 more source

DNA‐Templated 2D Heterostructures as Phototriggered Dynamic Nanohybrids: From Releasing Molecular Loads to Controlling Enzyme Biocatalytic Function

Advanced Functional Materials, EarlyView.
DNA strands are employed both as dynamic linkers and nanoscale templates for the integration of Ag2S nanoparticles on MoS2, which in turn imparted photothermal responsiveness; this feature permits the selective cargo (fluorophore, quantum dots or an enzyme) release from the MoS2 surface in response to local heat induced by light irradiation.
Kai Chen, Haosen Miao, Weiying Hong, Matteo Palma   +3 more
wiley   +1 more source