A new drag and lift correlation for spherocylinders from fully resolved Immersed Boundary Method
Abstract Many industrial processes deal with non‐spherical particles, e.g., mineral mining and biomass conversion. It is crucial to understand the particles' hydrodynamics to control and optimize these processes. To extend the current state‐of‐the‐art from arrays of spherical particles to spherocylindrical particles, we performed extensive particle ...
A. H. Huijgen +4 more
wiley +1 more source
PPO-Based Reinforcement Learning Control of a Flapping-Wing Robot with a Bio-Inspired Sensing and Actuation Feather Unit. [PDF]
Hussain S, Messaoudi M, Imran M, Tang D.
europepmc +1 more source
Automated generative process synthesis via transformer‐based dual‐loop simulation and optimization
Abstract This study presents a novel framework for automated generative process synthesis, addressing the complexity of simultaneously optimizing discrete topologies and continuous operating variables. To overcome conventional superstructure limitations, we propose a dual‐loop architecture integrating generative transformers with rigorous process ...
Yeong Woo Son +4 more
wiley +1 more source
Bayesian attenuation of offset analgesia filters out random disturbances in noxious stimuli. [PDF]
Ishikawa R, Osumi M, Izawa J.
europepmc +1 more source
Deep Learning‐Assisted Coherent Raman Scattering Microscopy
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
wiley +1 more source
Latitudinal Variation in Estuarine Archaeal Biogeography: Deterministic vs. Stochastic Assembly Processes and Network Stability Across China's Coastal Ecosystems. [PDF]
Liu Y +12 more
europepmc +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
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 +4 more
wiley +1 more source
Disturbance-tolerant quadrotor control using a hybrid LQR and super-twisting sliding mode approach. [PDF]
Budak S, Sungur C, Durdu A.
europepmc +1 more source
Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia +1 more
wiley +1 more source
Properties and ecological assembly mechanisms of microbial communities across salinity levels in coastal saline-alkaline soils. [PDF]
Ji C +7 more
europepmc +1 more source

