Results 81 to 90 of about 670,649 (179)

Accelerating Sustainable Epoxy Resin Development Through Bayesian Optimization and Inverse Design

Journal of Applied Polymer Science, Volume 143, Issue 37, October 5, 2026.
Development of a machine learning framework for the optimization of the Tg of partially bio‐based epoxy resin formulations in a 13‐component design space using Bayesian optimization, active learning, random design, and inverse design. The results show that the BO effectively navigates high‐dimensional formulation spaces, and the final ML model could ...
Natalie Wunder, Rodrigo Q. Albuquerque, Florian Max, Holger Ruckdäschel   +3 more
wiley   +1 more source

Influence of 3D Printing Parameters on ULTEM 9085 Mechanical Properties Using Explainable Machine Learning

SPE Polymers, Volume 7, Issue 4, October 2026.
An explainable machine‐learning framework predicts complete stress–strain behavior and key mechanical properties of FFF‐printed ULTEM 9085 from four printing parameters. Extra Trees delivered the most accurate and stable predictions, while SHAP and LIME clarified how each parameter influences material performance.
Md Asif Hasan, Mohammad Reza Chalak Qazani, Kassandra Herrnandez, Avijit Paul, Hadi Fathollahi Abdar, Mehdi Moayyedian, Houshyar Asadi, Devin J. Roach   +7 more
wiley   +1 more source

Numerical Investigation of the Mechanisms of Local Extinction Using Flame Kernel-Vortex interactions.

, 2006
The response of premixed flames to unsteady stretch is studied via kernel-vortex interactions. In this configuration a spark ignited kernel interacts with a vortex pair of variable strength. Both detailed and simple chemistry approaches are explored. In
Kolera-Gokula, Hemanth
core  

Benchmarking Auto‐Regressive Spatio‐Temporal Predictions of Wildfire Spread From the FireBench Simulation Data Set With a Machine Learning Competition

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 5, October 2026.
Abstract As wildfire severity increases, predicting wildfire spread is important for fire and landscape management. However, wildfire spread is a complex phenomenon that is challenging to capture because it depends on many factors, such as wind speed, slope, landscape topography, and fuel properties. Machine Learning (ML) models are powerful tools that
J. Z. Ho, A. Bazgir, A. Asaithambi, J. Hossain, R. Pawłowski, Z. Li, T. Dubail, Q. Wang, C. Gazen, B. Akoush, W. T. Chung, W. Reade, M. Ihme   +12 more
wiley   +1 more source

Insights into the effects of reproductive phase thermal stress on physiology and yield‐related traits of rice cultivars

Agrosystems, Geosciences &Environment, Volume 9, Issue 3, September 2026.
Abstract High temperatures lead to a significant drop in rice (Oryza sativa L.) productivity worldwide, especially during the reproductive stage. This research was piloted to evaluate 10 promising rice cultivars for their ability to withstand high‐temperature stress (HS) during the reproductive phase and to assess the impact on physiology and yield ...
Summiya Faisal, Noor Elahi Jan, Zainab Hussain, Muhammad Shahbaz Farooq, Abdul Shakoor, Umsalama A. H. Ahmed, Muataz Ahmed Abdalla, Badr Alharthi, Sajid Fiaz, Lubna Fareed   +9 more
wiley   +1 more source

Propagation characteristics of H2–air detonations in double-bend ducts

Frontiers in Mechanical Engineering
Detonation transmission through compact piping and transition cavities is frequently limited by diffraction-induced shock–flame decoupling, which can lead to either recovery or complete failure depending on the available confinement and reflection ...
Yuhan Wang, Chun Zheng, Huanhao Zhang, Zhihua Chen   +3 more
doaj   +1 more source

Prognostic Approaches for Early Detection of Thermal Runaway in Lithium‐Ion Batteries

Battery Energy, Volume 5, Issue 5, September 2026.
This article reviews methodologies for early detection of thermal runaway in lithium‐ion batteries, focusing on thermal, electrical, mechanical, and gas‐based precursors. It compares detection performance, reliability, lead time, and system‐level integration challenges to guide the development of practical, robust prognostic safety architectures.
Sahithi Maddipatla, Byoungchul Kwon, Judith Jeevarajan, Michael Pecht   +3 more
wiley   +1 more source

In Vitro Anti‐Inflammatory Activity of Sour Cherry (Prunus cerasus L.) Seed Oil and Computational Safety Profiling

Chemistry &Biodiversity, Volume 23, Issue 9, September 2026.
In vitro anti‐inflammatory activity of sour cherry (Prunus cerasus L.) seed oil and computational safety profiling. ABSTRACT This study aimed to evaluate the in vitro anti‐inflammatory activity of sour cherry seed oils, including samples obtained by Soxhlet extraction and maceration, as well as ten commercial samples.
Tuğba Aydin, Tuğba Günbatan, Aysel Berkkan, Onur Kenan Ulutaş, Melike Sucu   +4 more
wiley   +1 more source

Effects of Soret Diffusion and Radiative Heat Loss on the Evolution of Buoyant Flame Kernels in Ultra-Lean Hydrogen-Air Mixture

Fire
Ultra-lean hydrogen flames under terrestrial gravity are governed by a coupled interaction among preferential diffusion, thermal diffusion, heat loss, and self-induced convection.
Ivan S. Yakovenko, Alexey D. Kiverin
doaj   +1 more source

Evaluation of Explosion Puffed Rice for Beer Production: Increased Wort Yield at the Cost of Filtration Performance

Cereal Chemistry, Volume 103, Issue 5, Page 812-817, September/October 2026.
ABSTRACT Background and Objectives Explosion puffing, a new pretreatment technology, was first applied to rice as a beer adjunct to replace conventional cooking and explore its potential to improve saccharification efficiency. Findings Explosion puffed rice exhibited reduced moisture, bulk density, starch, and fat, with a 5.37‐fold increase in ...
Qi Pan, Jiangyu Zhu, Yongqi Yin, Zhengfei Yang   +3 more
wiley   +1 more source