Results 121 to 130 of about 4,562,869 (259)

Modeling heat and mass transfer in Williamson nanofluid stagnation flow: Influence of porosity, chemical reaction, and internal heating

Chemical Engineering Journal Advances
Stagnation point flow of non-Newtonian fluids is crucial in understanding fluid behaviour in cooling systems, thrust bearings and other applications involving polymers and suspensions.2,2 The present work explores the heat and mass transfer for ...
Shital Sobale, Jagadish V. Tawade, Ali B.M. Ali, Dana Mohammad Khidhir, Muyassar Norberdiyeva, F.F. Al-Harbi, Nitin Satpute, Nidhal Ben Khedher   +7 more
doaj   +1 more source

Entropy generation in magneto couple stress bionanofluid flow containing gyrotactic microorganisms towards a stagnation point on a stretching/shrinking sheet. [PDF]

Sci Rep, 2023
Khan MS, Shah Z, Roman M, Khan W, Vrinceanu N, Alshehri MH.   +5 more
europepmc   +1 more source

Artificial Intelligence‐Driven Network Pharmacology: A Methodological Paradigm Shift Bridging Traditional Wisdom and Modern Science

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence is redefining network pharmacology (NP). By integrating knowledge graph engineering, geometric deep learning, multiomics anchoring, and generative reasoning, AI‐driven NP (AI‐NP) transforms static target mapping into dynamic, predictive modeling.
Cong Wang, Sile Hu, Rigahai Ji, Riguna A, Siqige Hao, Ma Zhuo, Yi‐Hung Chen, Bisihalatu Hu, Ulana Bai, Xigui Hada   +9 more
wiley   +1 more source

Unsteady mix convectional stagnation point flow of nanofluid over a movable electro-magnetohydrodynamics Riga plate numerical approach. [PDF]

Sci Rep, 2023
Nasir S, Berrouk AS, Gul T, Zari I, Alghamdi W, Ali I.   +5 more
europepmc   +1 more source

Crystal Structure Prediction of Inorganic Materials: A Benchmark and Modern Evaluation

Advanced Intelligent Discovery, EarlyView.
Predicting a crystal’s structure from composition alone is a long‐standing challenge in materials discovery. The CSP180 benchmark of 180 inorganic crystals evaluates thirteen crystal structure prediction algorithms requiring no density functional theory (DFT) against DFT‐based baselines across twelve metrics.
Lai Wei, Sadman Sadeed Omee, Rongzhi Dong, Nihang Fu, Yuqi Song, Edirisuriya M. Dilanga Siriwardane, Meiling Xu, Ming Hu, Chris Wolverton, Jianjun Hu   +9 more
wiley   +1 more source

Oblique stagnation point flow of magnetized Maxwell fluid over a stretchable Riga plate with Cattaneo-Christov heat flux and convective conditions. [PDF]

Sci Rep, 2023
Baig MNJ, Salamat N, Akhtar S, Nadeem S.
europepmc   +1 more source

Sound‐Based Assembly of Magnetically Actuated Soft Robots Toward Enhanced Release of Extracellular Vesicles

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Magnetic soft robots offer promise in biomedicine due to their wireless actuation and rapid response, but current fabrication methods are complex and have limited cellular compatibility. A new, contactless bioassembly strategy using hydrodynamic instabilities is introduced, enabling customizable, centimeter‐scale robots.
Wei Gao, Riccardo Tognato, Micaela Natta, Elena Della Bella, Alessandro Cianciosi, Tiziano Serra   +5 more
wiley   +1 more source

Spherical Hybrid Nanoparticles for Homann Stagnation-Point Flow in Porous Media via Homotopy Analysis Method. [PDF]

Nanomaterials (Basel), 2023
You X, Cui J.
europepmc   +1 more source

A NEAT Approach to Evolving Neural‐Network‐Based Optimization of Chiral Photonic Metasurfaces: Application of a NeuroEvolution‐of‐Augmenting‐Topologies Pipeline

Advanced Intelligent Systems, EarlyView.
Neuro‐evolution can boost machine‐learning optimization of chiral metasurfaces. By integrating the NEAT algorithm into a deep‐learning framework, we enable the efficient design of visible‐spectrum chiroptical responses. NEAT autonomously evolves neural‐network architectures and weights, reducing manual tuning.
Davide Filippozzi, Arash Rahimi‐Iman
wiley   +1 more source

Irreversibility analysis with hybrid cross nanofluid of stagnation point and radiative flow ( T i O 2 + C u O ) based on engine oil past a stretchable sheet. [PDF]

Heliyon, 2023
Lone SA, Ali F, Saeed A, Bognár G.
europepmc   +1 more source