Results 81 to 90 of about 9,329 (266)

Unique Aerofoil‐Structured Microfluidics for High Throughput Lipid Nanoparticle Formulation Screening and Scale‐up

open access: yesAdvanced Science, EarlyView.
This study presents aerofoiled microfluidic structures optimized for efficient mixing and lipid nanoparticle (LNP) formation across broad flow rates. Based on this design, two dedicated systems are introduced: MiNANO‐form for high‐throughput formulation screening and MiNANO‐scale for continuous large‐scale production, enabling reproducible, high ...
Dongsheng Liu   +8 more
wiley   +1 more source

Experimental Investigation of Diluents Components on Performance and Emissions of a High Compression Ratio Methanol SI Engine

open access: yesEnergies, 2019
Increasing compression ratio and using lean burn are two effective techniques for improving engine performance. Methanol has a wide range of sources and is a kind of suitable fuel for a high-compression ratio spark-ignition lean burn engine.
You Zhou   +5 more
doaj   +1 more source

Performance of Combustion and Emissions Characteristics of Ethanol Dual Injection Spark Ignition Engine

open access: diamond, 2021
Nizar F O Al-Muhsen   +5 more
openalex   +1 more source

Tailored Electro–Magnetic–Porous Multigradient Nanoarchitectonics for Absorption‐Dominated Electromagnetic Interference Shielding and Adaptive Multifunctionality

open access: yesAdvanced Science, EarlyView.
An electro–magnetic–porous multigradient nanofibrous electromagnetic interference (EMI) membrane is fabricated via shear‐induced in situ fibrillation and layer‐by‐layer assembly. Leveraging a multigradient‐induced “impedance matching–polarization–reabsorption” synergistic mechanism, the membrane achieves absorption‐dominated high‐efficiency EMI ...
Runze Shao   +5 more
wiley   +1 more source

Performance Evaluation of Multi-Fuel Spark Ignition Engines [PDF]

open access: bronze, 1999
Metwally Moussa   +5 more
openalex   +1 more source

Thermal Runaway Temperature Prediction of Lithium‐Ion Battery Under Extreme High‐Temperature Shock Using Experimental and Virtual Data

open access: yesAdvanced Science, EarlyView.
An integrated framework predicts lithium‐ion batteries (LIB) thermal runaway (TR) under extreme high‐temperature shock. By combining experimental data with the multiphysics‐generated virtual data, a hybrid deep learning approach is developed to accurately forecast temperature evolution for unseen scenarios.
Xiaoyu Li   +6 more
wiley   +1 more source

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