Results 211 to 220 of about 15,852,142 (311)

Gas–liquid mass transfer enhancement in the presence of nanoparticles under slug flow in microreactors

AIChE Journal, EarlyView.
Abstract Nanofluids containing nanoparticles represent a promising solvent or reaction system for gas–liquid operations. Herein, the effect of nanoparticle (Al2O3 and SiO2) addition on gas–liquid slug flow pattern and mass transfer enhancement was investigated during CO2 absorption into water in microreactors.
Jie Zong, Jun Yue
wiley   +1 more source

Maximal Dissipation and Well-Posedness of the Euler System of Gas Dynamics. [PDF]

Arch Ration Mech Anal
Feireisl E, Jüngel A, Lukáčová-Medvid'ová M.   +2 more
europepmc   +1 more source

Universally Accurate or Specifically Inadequate? Stress‐Testing General Purpose Machine Learning Interatomic Potentials

Advanced Intelligent Discovery, EarlyView.
We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob, Karsten Reuter, Johannes T. Margraf   +2 more
wiley   +1 more source

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

Advanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi, Kateryna Andriienkova, Tetyana Goldanova, Ezgi Antmen, Thibaut Soubrie, Nihal Engin Vrana   +5 more
wiley   +1 more source

Optimal α/β Ratio for Biologically Effective Dose-Based Prediction of Radiation-Induced Peritumoral Brain Edema in Meningioma. [PDF]

Cancers (Basel)
Ko SW, Won YD, Ha BJ, Cheong JH, Ryu JI, Hong SW, Min KW, Han MH.   +7 more
europepmc   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source

X-ray computed tomography images of wheat kernels and reconstructed three-dimensional shapes. [PDF]

Sci Data
Shi Z, Wang M, Xie Y, Gao B, Wang T.
europepmc   +1 more source

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

Advanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas, Panagiotis Krokidas, Vasileios Vavourakis, Clara Essmann, George Giannakopoulos   +4 more
wiley   +1 more source

Extending voxel-based lesion mapping to neurosurgical oncology: applications in intracranial meningiomas. [PDF]

Front Oncol
Spolaore A, Wang S, Machetanz K, Tatagiba M, Naros G.   +4 more
europepmc   +1 more source

Real‐Time Multicolor Fluorescence Microscopy via Cross‐Channel Acquisition and Deep‐Learning‐Based Inference

Advanced Intelligent Discovery, EarlyView.
Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto, Yuxin Jin, Nicholas Roy, Sarthak Misra   +3 more
wiley   +1 more source