Вход на сайт

Просмотр новости

Найдите то, что Вас интересует

Predictive Degradation Modelling of Solar Encapsulants: A Deep Learning Approach to IEC 61215 Thermal Cycling

Дата публикации: 22-10-2026 06:50:49

An article created on 2026-10-22 06:50:49

Схожие новости

#Наименование новостиТональностьИнформативностьДата публикации
1Physics-guided auxiliary multi-task learning for temperature-dependent thermoelectric 𝑧𝑇 curve prediction03521-10-2026
2Evaluation of Machine Learning Models for Geothermal Downhole Temperature Prediction Using Hydrogeochemical Datasets015.2620-10-2026
3From Soft to Hard Constraints in Physics-Informed Extreme Learning Machines: Analysis and Algorithms020.5322-10-2026
4Physics-Informed Support Vector Regression for Predicting Copolymer LCST Depressions via Thermodynamic Hofmeister Featurization020.5321-10-2026
5Battery-Aware Finsler Geometry for Energy-Optimal Routing of Electric Vehicles03022-10-2026
6Physics-Based Performance Mapping of Ultra-High-Voltage SiC IGBTs and MOSFETs With Machine-Learning Acceleration032.2221-10-2026
7Hybrid Electrochemical-Photochemical System for Metformin Hydrochloride Degradation: Operational Optimization, Kinetics and Toxicity Assessment020.5321-10-2026
8One-pot synthesis of carbon nanotube/graphene composite phase change materials based on Pickering emulsion for solar thermal storage017.4721-10-2026
9A Passive Voltage Spike Suppression Strategy for High-Frequency Link Inverters Based on Primary-Side Resonance023.2822-10-2026
10Machine Learning-Assisted Thermal Performance Enhancement of Compact Salinity Gradient Solar Ponds Using Hybrid Nanoparticle-Enhanced Phase Change Materials023.0419-08-2026

Классификация: Наука. Схожих патентов: 0. Схожих новостей: 10. Тональность: 0. Информативность: 19.52. Источник: www.researchsquare.com.