Results 101 to 110 of about 12,964 (262)

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
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, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

On plane polynomial vector fields and the Poincaré problem

Electronic Journal of Differential Equations, 2002
Summary: We address the Poincaré problem, on plane polynomial vector fields, under some conditions on the nature of the singularities of invariant curves. Our main idea consists in transforming a given vector field of degree \(m\) into another one of degree at most \(m+1\) having its invariant curves in projective quasi-generic position. This allows us
openaire   +3 more sources

Consumer Preferences for Craft Beer: The Interplay of Localness and Advertising Language

Agribusiness, EarlyView.
ABSTRACT This study explores the influence of the language of the label, origin of production, and origin of brewing ingredients on Croatian consumers' preferences and willingness to pay for organic craft beer. Employing an online survey and a choice experiment among 223 Croatian alcohol consumers, we find that while there's a willingness to pay a ...
Marija Cerjak, Claudia Bazzani, Andreas C. Drichoutis   +2 more
wiley   +1 more source

Determinants of Knowledge and Usage of Generative Artificial Intelligence in Agricultural Extension: Evidence From Tennessee Extension Personnel

Agribusiness, EarlyView.
ABSTRACT This paper examines the determinants of generative AI (GenAI) knowledge and usage among agricultural extension professionals. Drawing on survey data from agricultural extension personnel in Tennessee, we employ regression analyses and latent Dirichlet allocation (LDA) for topic modeling of open‐ended responses to study the knowledge and usage ...
Abdelaziz Lawani, Jason de Koff, James Muriuki, Anna‐Liisa Ihuhwa   +3 more
wiley   +1 more source

Is There a Market for Organic Milk in Serbia? Insights From Integrated Choice and Latent Variable Model

Agribusiness, EarlyView.
ABSTRACT Past growth in the global organic market has been concentrated in high‐income countries, while in middle‐income countries such as Serbia the organic market remains nascent and characterized by a sparse assortment of organic products, high retail premia and limited evidence on consumer preferences and their drivers.
Milan Tatic, Sanja Dzever, Bojan Matkovski, Danilo Djokic   +3 more
wiley   +1 more source

A computational study of Ising‐based solvers for discrete landscape exploration in process optimization

AIChE Journal, EarlyView.
ABSTRACT Conceptual process design combines discrete configuration choices with continuous operating decisions, often yielding difficult mixed‐integer nonlinear or simulation‐based optimization problems. This work presents an exploratory computational assessment of Ising‐based solvers, simulated annealing, quantum annealing, and entropy computing, as ...
Yirang Park, David E. Bernal Neira
wiley   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

An Enhanced Gas Sensor Data Classification Method Using Principal Component Analysis and Synthetic Minority Over-Sampling Technique Algorithms

Micromachines
This study addresses the challenge of multi-dimensional and small gas sensor data classification using a gelatin–carbon black (CB-GE) composite film sensor, achieving 91.7% accuracy in differentiating gas types (ethanol, acetone, and air). Key techniques
Xianzhang Zeng, Muhammad Shahzeb, Xin Cheng, Qiang Shen, Hongyang Xiao, Cao Xia, Yuanlin Xia, Yubo Huang, Jingfei Xu, Zhuqing Wang   +9 more
doaj   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
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, Christian Mark Pelicano   +1 more
wiley   +1 more source