Results 171 to 180 of about 74,327 (228)

Hydrophobic eutectic solvent‐engineered membranes for highly permeable, selective, and antifouling pharmaceutical removal from municipal wastewater

open access: yesENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
Single‐step incorporation of a hydrophobic deep eutectic solvent (HDES) into polyethersulfone ultrafiltration membranes via non‐solvent induced phase separation creates selective, antifouling membranes for pharmaceutical removal. The HDES nanodomains enhance permeability, electrostatic interactions, and adsorption affinity, enabling efficient and ...
Anjali Goyal   +8 more
wiley   +1 more source

Machine Learning and Artificial Intelligence Techniques for Intelligent Control and Forecasting in Energy Storage‐Based Power Systems

open access: yesEnergy Science &Engineering, EarlyView.
A new energy paradigm assisted by AI. ABSTRACT The tremendous penetration of renewable energy sources and the integration of power electronics components increase the complexity of the operation and power system control. The advancements in Artificial Intelligence and machine learning have demonstrated proficiency in processing tasks requiring ...
Balasundaram Bharaneedharan   +4 more
wiley   +1 more source

Design framework for programmable three-dimensional woven metamaterials. [PDF]

open access: yesNat Commun
Carton M   +4 more
europepmc   +1 more source

Design of HAWT Rotor for Non‐Uniform Inflow Conditions: A Theoretical and Experimental Approach for Shear Flow

open access: yesEnergy Science &Engineering, EarlyView.
This paper aims to provide a robust design approach for HAWTs operating in shear flow. This study fills a critical research gap by integrating BEM and vortex theories for blade design in non‐homogeneous inflow conditions. The authors of the paper made an effort to develop and test an experimentally unsophisticated model of a turbine working in shear ...
Agnieszka Dorota Woźniak   +2 more
wiley   +1 more source

Electricity Price Prediction Using Multikernel Gaussian Process Regression Combined With Kernel‐Based Support Vector Regression

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT This paper presents a new hybrid model for predicting German electricity prices. The algorithm is based on a combination of Gaussian process regression (GPR) and support vector regression (SVR). Although GPR is a competent model for learning stochastic patterns within data and for interpolation, its performance for out‐of‐sample data is not ...
Abhinav Das   +2 more
wiley   +1 more source

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