Results 61 to 70 of about 11,890 (266)

Metal–Organic Frameworks for Gaseous Pollutant Management: From Capture to Neutralization and Reutilization

Advanced Functional Materials, EarlyView.
This review maps how MOFs can manage hazardous gases by combining adsorption, neutralization, and reutilization, enabling sustainable air‐pollution control. Covering chemical warfare agent simulants, SO2, NOx, NH3, H2S, and volatile organic compounds, it highlights structure‐guided strategies that boost selectivity, water tolerance, and cycling ...
Yuanmeng Tian, Zeyu Tao, Kaikai Ma, Xiaoliang Wang, Bo Yu, Yiu Wan Yip, Zhijie Chen, Jin Shang, Bin Fei   +8 more
wiley   +1 more source

Effective Modeling of CO₂ Emissions for Light-Duty Vehicles: Linear and Non-Linear Models with Feature Selection

Energies
Predictive modeling is important for assessing and reducing energy consumption and CO2 emissions of light-duty vehicles (LDVs). However, LDV emission datasets have not been fully analyzed, and the rich features of the data pose challenges in prediction ...
Hang Thi Thanh Vu, Jeonghan Ko
doaj   +1 more source

A Comparative Study of Actual Fuel Consumption and the Predicted Fuel Consumption of the Tractor with Chisel Plow

, 2021
A field experiment was conducted during December 2019, at the Demonstration Farm of the Faculty of Natural Resources and Environmental Studies, University of Alsalam. The objective was to compare the actual fuel consumption and the predicted fuel consumption of tractor with chisel plow.
Suliman, Ayman Hassan, Saeed, Amir Bakheit, Moayad Mohamed Balel   +2 more
openaire   +1 more source

Evaluation of the Dual Impact of Nanotechnologies on Health and Environment Through Alternative Bridging Models

Advanced Healthcare Materials, EarlyView.
This review explores how alternative invertebrate and small‐vertebrate models advance the evaluation of nanomaterials across medicine and environmental science. By bridging cellular and organismal levels, these models enable integrated assessment of toxicity, biodistribution, and therapeutic performance.
Marie Celine Lefevre, Margherita Bernardeschi, Matteo Battaglini, Gianni Ciofani   +3 more
wiley   +1 more source

Research on Energy Saving for Hybrid Tractor Based on Working Condition Prediction and DDPG-Fuzzy Control

World Electric Vehicle Journal
To significantly reduce fuel consumption and improve fuel economy in hybrid tractor under complex working conditions, an energy—saving strategy based on working condition prediction and Deep Deterministic Policy Gradient and Fuzzy control (DDPG-Fuzzy ...
Shilong Fan, Xianghai Yan, Shuaishuai Ge, Junjiang Zhang, Mengnan Liu   +4 more
doaj   +1 more source

Predicting Ship Fuel Consumption: Update

, 1996
This report is concerned with the prediction of ship propulsion fuel consumption as a function of ship speed for U.S. Navy combatant and auxiliary ships. Prediction is based on fitting an analytic function to published ship class speed-fuel use data using nonlinear regression.
Schrady, David A., Smyth, Gordon K., Vassian, Robert Bruce   +2 more
openaire   +1 more source

Nanotherapies for Atherosclerosis: Targeting, Catalysis, and Energy Transduction

Advanced Healthcare Materials, EarlyView.
Atherosclerosis management is hindered by poor drug targeting and plaque heterogeneity. Nanotechnology overcomes these barriers via three core strategies: (1) target‐engineered nanocarriers that achieve lesion‐specific precision via ligand modification, biomimetic camouflage, stimuli‐responsive release, and self‐propelling nanomotors; (2) catalytic ...
Yuqi Yang, Jingguo Qu, Tonghuan Xiao, Xinyang Han, Michael Tin‐Cheung Ying   +4 more
wiley   +1 more source

Mesoporous Silica Nanoparticles in Biomedicine: Advances and Prospects

Advanced Materials, EarlyView.
Mesoporous silica nanoparticles offer unique properties like high surface area, tunable pores, and functionalization. They excel in drug delivery, tissue engineering, and stimuli‐responsive therapies, enabling targeted and controlled treatments. With roles in cancer therapy and diagnostics, their clinical translation requires addressing challenges in ...
Miguel Manzano, María Vallet‐Regí
wiley   +1 more source

Energy parameter modeling in plug-in hybrid electric vehicles using supervised machine learning approaches

e-Prime: Advances in Electrical Engineering, Electronics and Energy
In this study, supervised machine learning techniques like random forest (RF), K-nearest neighbour (KNN), multiple linear regression (MLR), and artificial neural networks (ANNs) were used to predict energy parameters in plug-in hybrid electric vehicles ...
Bukola Peter Adedeji
doaj   +1 more source

Atomistic Mechanisms Triggered by Joule Heating Effects in Metallic Cu‐Bi Nanowires for Spintronics

Advanced Materials, EarlyView.
Bi doped metallic Cu nanowires are promising for spintronics thanks to the stabilization of a giant spin Hall effect. However, heat resulting from current injection forces Bi to leave solution, forcing segregation into monoatomic decorations which evolve into coherent crystalline aggregates.
Alejandra Guedeja‐Marrón, Juan Ignacio Beltrán, Matilde Saura‐Múzquiz, Paolo Perna, M. Carmen Muñoz, Lucas Pérez, Maria Varela   +6 more
wiley   +1 more source