Results 161 to 170 of about 34,690 (269)
A Mathematical Analysis of IPT-DMFT. [PDF]
Cancès E, Kirsch A, Perrin-Roussel S.
europepmc +1 more source
Topological Properties of International Commodity Market: How Uncertainty Affects the Linkages?
ABSTRACT The study aims to explore the network topology of the international commodity market by examining the interconnections among 21 commodity futures across various categories, including energy, precious and industrial metals, and agriculture. We analyze the market structure of these commodity futures under both low and high uncertainty conditions
Ibrahim Yagli, Bayram Deviren
wiley +1 more source
Structure-efficiency relationship of access group antibiotics via SK chromatic descriptors. [PDF]
Rajambigai R, Praveen T, Ravi Sankar J.
europepmc +1 more source
Cost‐Benefit Analysis of the European Union Carbon Border Adjustment Mechanism in Fertilizer Trade
ABSTRACT The carbon border adjustment mechanism (CBAM), launching 2026, will charge EU importers for embedded carbon emissions, aiming to reduce emissions but raising import costs. Shifts in demand following implementation may reduce carbon emissions, but importers will bear the cost of increased prices.
Natalie Crisci +3 more
wiley +1 more source
Some Properties of the Plaquette Random-Cluster Model. [PDF]
Duncan P, Schweinhart B.
europepmc +1 more source
AI in chemical engineering: From promise to practice
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew +4 more
wiley +1 more source
Linear model based on neighborhood ABS index for graph energy in benzenoid hydrocarbons and maximum index cactus graphs. [PDF]
Chu ZQ +3 more
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
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 +2 more
wiley +1 more source

