Results 131 to 140 of about 1,130,906 (218)

Suppressing electron-phonon coupling and energy loss in organic solar cells by modulating donor-acceptor penetrated-interface. [PDF]

Nat Commun
Luo Y, Hai Y, Li Y, Ma R, Wu L, Fan K, Chan Y, Dela Peña TA, Dong F, Wang M, Lam YM, Yan H, Wong KS, Jia T, Li G, Wu J.   +15 more
europepmc   +1 more source

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

Demonstration of angular-momentum-resolved electron energy-loss spectroscopy. [PDF]

Nat Commun
Tavabi AH, Rosi P, Bertoni G, Rotunno E, Belsito L, Roncaglia A, Frabboni S, Gazzadi GC, Karimi E, Tiemeijer P, Dunin-Borkowski RE, Grillo V.   +11 more
europepmc   +1 more source

Optimization of the Production of Rubber Compounds Using Mathematical Models

Advanced Engineering Materials, EarlyView.
Rubber compounds were mixed in a batch internal mixer, and symbolic regression was used to derive mathematical models linking recipe and process parameters to ram path, torque, and mixing quality (incorporation, dispersion, distribution). Subsequent optimization with evolutionary algorithms identified operating conditions that reduce specific energy ...
Anke Bardehle, Andreas Limper, Ulrich Giese, Carlos Lucke, Mario Beiner, Christoph Gögelein, Lisa Leuchtenberger‐Engel, Christian Hopmann   +7 more
wiley   +1 more source

Rational Asymmetric Acceptor Engineering via Unidirectional Terminal π-Extension and Optimizing Alkyl Branching Sites Affords a Binary Photovoltaic Efficiency of 20.7% by Suppressed Nonradiative Energy Loss. [PDF]

Adv Mater
Zhang H, Li Y, Sun K, Fu J, Liu FK, Zhi HF, Li EL, Zhang Z, Ai J, Kang MG, Woo HY, Wang Y, Song Y, Song Y, An Q, Zhang G, Chen H, Li G, Wang JL.   +18 more
europepmc   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Optimal design and operation of Photovoltage distributed generators and shunt compensators for the Vietnam alternative current distribution network to reduce annual energy loss. [PDF]

PLoS One
Duong MP, Nguyen BN, Arkhincheev V, Nguyen TT.   +3 more
europepmc   +1 more source

Inverse Identification of Energy‐Dependent Laser Absorptivity in NiTi Laser Powder‐Bed Fusion via Calibrated Melt Pool Simulation

Advanced Engineering Materials, EarlyView.
A combined experimental–computational framework identifies energy‐dependent laser absorptivity for NiTi in laser powder‐bed fusion, applicable to conduction and transition modes. Single‐track experiments and thermofluid smoothed particle hydrodynamics simulations are coupled through inverse analysis of melt pool geometry.
Mohamadreza Afrasiabi, Hadi Moutablaleh, Ignatius A. Setiawan, Mehrshad Mehrpouya   +3 more
wiley   +1 more source

Evaluation of Blood Flow Energy Loss before and after Endovascular Aneurysm Repair Using Four-dimensional Flow MR Imaging. [PDF]

Magn Reson Med Sci
Ikeda S, Mine T, Sekine T, Abe M, Ito H, Okada K, Happoh S, Ueshima S, Tomoda T, Fujii M, Hayashi H, Kumita SI.   +11 more
europepmc   +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