Results 41 to 50 of about 78,546 (297)

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

Leveraging Domain-Specific Features for High-Performance Obstacle Classification in Railway Monitoring

IEEE Access
Railway systems are among the most important transportation routes. Due to their vastness, limited evasion possibilities for trains, and their long braking distances, ensuring the safety of these networks is challenging and can be improved through the ...
Luca Eisentraut, Merlin Schadt, Christopher Mai, Walter Koehn, Ricardo Buettner   +4 more
doaj   +1 more source

Influence of Geometric Design on Mechanical Performance of Auxetic Metastructure

Advanced Engineering Materials, EarlyView.
Strategic geometric reinforcement transforms auxetic performance. This study evaluates 3D‐printed arrowhead metastructures, revealing that a modified design with local ring reinforcement suppresses premature failure to achieve superior energy absorption and structural efficiency.
Muhammad Gulzari, Supharoek Sornsomrit, Muhammad Ayaz Akbar, Stephan Rudykh   +3 more
wiley   +1 more source

To Combine or Not to Combine? The Influence of Combining Training Datasets on the Robustness of Deep Learning Models: An Analysis for Optical Character Recognition of Handwriting

IEEE Access
The present manuscript addresses the question of how training data should be sampled for deep learning models by analyzing and evaluating the impact of training data representation and complexity on the performance and robustness of deep learning models.
Leopold Fischer-Brandies, Lucas Muller, Benjamin Rebholz, Ricardo Buettner   +3 more
doaj   +1 more source

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

Deep-Learning-Based Determination of Textile Properties: A Novel Triplet Architecture Approach for Classifying Cotton Content

IEEE Access
To reach sustainable production and consumption patterns, recycling is a key task. Automating the recycling process, especially in sorting tasks, is a strong hope to improve the efficiency and economic viability of the recycling industry.
Max Wiedemann, Pascal Penava, Christopher Mai, Ricardo Buettner   +3 more
doaj   +1 more source

Oxygen‐Tunnel Indium Tin Oxide Vertical Channel Transistors with Enhanced Current Density and Reliability for Monolithic 3D Compute‐In‐Memory Systems

Advanced Functional Materials, EarlyView.
Oxygen‐tunnel (OT) indium tin oxide (ITO) vertical channel transistors (VCTs) enable reliable, high‐density gain‐cell memory for monolithic 3D integration. A sandwiched SiN/SiO2/SiN OT stack selectively regulates oxygen transport, suppressing parasitic electrode oxidation while stabilizing channel oxygen vacancies, thereby suppressing carrier injection
Hyeonho Gu, Haksoon Jung, Yongwoo Lee, Hoichang Jeong, Yanfeng Zhao, Heesoo Yang, Minho Park, Hyeonjin Lee, Seunghun Baek, Minju Song, Junghwan Kim, Youngmin Jo, Hyunjin Park, Munhyeon Kim, Jae‐Joon Kim, Kyuho Jason Lee, Byungjo Kim, Jimin Kwon   +17 more
wiley   +1 more source

Fresh or Rotten? Enhancing Rotten Fruit Detection With Deep Learning and Gaussian Filtering

IEEE Access
We address the pressing issue of food waste by proposing a robust image classification model that can reliably detect rotten fruits. More than half of the fruit yield is lost along the supply chain, with post-harvest losses due to rottenness playing a ...
Leopold Fischer-Brandies, Lucas Muller, Justus Johannes Riegger, Ricardo Buettner   +3 more
doaj   +1 more source

Geometry of turbulent dissipation and the Navier–Stokes regularity problem

Scientific Reports, 2021
The question of whether a singularity can form in an initially regular flow, described by the 3D incompressible Navier–Stokes (NS) equations, is a fundamental problem in mathematical physics. The NS regularity problem is super-critical, i.e., there is a ‘
Janet Rafner, Zoran Grujić, Christian Bach, Jakob Andreas Bærentzen, Bo Gervang, Ruo Jia, Scott Leinweber, Marek Misztal, Jacob Sherson   +8 more
doaj   +1 more source

Solution‐Processed Two‐Dimensional Indium Oxide on Sodium‐Embedded Alumina for Reconfigurable Optoelectronic Synaptic Transistors

Advanced Functional Materials, EarlyView.
Wafer‐scale two‐dimensioanl In2Se3 oxidized into InOx on sodium‐embedded beta‐alumina enables multifunctional reconfigurable electronics. Sodium ions accumulate within distinct spatial distribution under drain‐controlle and gate‐controlled operation. Drain‐control operation gives controllability of ultraviolet‐driven optoelectronic synaptic conductance
Jinhong Min, Yonghyun Albert Kwon, Hyunbin Kim, Jihyun Kim, Myeongjin Jung, Jaewon Heo, Gwang Ya Kim, Vlastimil Mazanek, Zdeněk Sofer, In Soo Kim, Jeong Ho Cho, Hyesung Park, Sang Min Won, Joohoon Kang   +13 more
wiley   +1 more source