Results 71 to 80 of about 16,931 (262)
To accelerate the inverse design of heterostructured metal matrix composites, a closed‐loop scientific machine learning framework integrates continual learning prediction with NSGA‐II‐PMCP optimization. The framework maps microstructural descriptors to strength, toughness, and modulus, expands high‐quality Pareto solutions, and guides experimentally ...
Zhiyan Zhong +11 more
wiley +1 more source
Automation and Active Learning for the Multi‐Objective Optimization of Antibody Formulations
Successful antibody formulation necessitates balancing factors such as thermal stability, colloidal stability, and viscosity across a vast excipient design space. This work integrates robotic liquid handling, high‐throughput biophysical characterization, and multi‐objective Bayesian optimization in an iterative closed‐loop Design‐Build‐Test‐Learn cycle.
D. Christopher Radford +3 more
wiley +1 more source
The Gumbel- Pareto Distribution: Theory and Applications
In this paper, for the first time we introduce a new four-parameter model called the Gumbel- Pareto distribution by using the T-X method. We obtain some of its mathematical properties. Some structural properties of the new distribution are studied.
Saad et al.
doaj +1 more source
Data‐Driven Design of Self‐Adhesive Epidermal Electrodes and Sensors
This work presents self‐adhesive, stretchable epidermal electrodes and sensors developed through a data‐driven design framework that integrates artificial neural networks with genetic algorithms. By tailoring optimization objectives, either maximizing electrical conductivity and adhesion or enhancing piezoresistive sensitivity, the study enables the ...
Xuan Li +10 more
wiley +1 more source
On estimation of P(Y < X) for inverse Pareto distribution based on progressively first failure censored data. [PDF]
Alharbi R +4 more
europepmc +1 more source
Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization
Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali +3 more
wiley +1 more source
The reliability analysis based on the generalized intuitionistic fuzzy two-parameter Pareto distribution. [PDF]
Roohanizadeh Z +2 more
europepmc +1 more source
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen +4 more
wiley +1 more source
ABSTRACT We conducted two framed field economic experiments with citrus farmers in Florida, United States and soybean farmers in Argentina to investigate their willingness to coordinate pest and weed management efforts. Despite the contrast between these two agricultural contexts, we find striking behavioral commonalities.
Ariel Singerman, Sergio H. Lence
wiley +1 more source
Baseline Methods for the Parameter Estimation of the Generalized Pareto Distribution. [PDF]
Martín J +3 more
europepmc +1 more source

