Results 181 to 190 of about 13,501 (263)

Hydrosilane Chemistry: From Historic First Steps to Modern Applications

open access: yesEuropean Journal of Inorganic Chemistry, EarlyView.
This review covers the history of hydrosilanes, from their initial discovery to their modern applications. It highlights the pioneering work of chemists like Alfred Stock and Franz Fehér and discusses the modern ways of synthesis and use of hydrosilanes in printed electronics.
Uwe Böhme, Maik Gerwig
wiley   +1 more source

Nanophotonic Biosensors and the Paradigm of Trans‐Scale Autonomous Bio‐Integrated Diagnostics for Addressing Health Complexities

open access: yesElectron, EarlyView.
Physics‐driven advances in optical nanobiosensors for rapid, miniaturized, and point‐of‐care diagnostics for next‐generation decentralized and personalized healthcare based on sensor intelligence. ABSTRACT Public health emergencies and the escalating burden of chronic diseases necessitate a paradigm shift from centralized laboratory testing to rapid ...
Vishal Chaudhary   +5 more
wiley   +1 more source

Enabling Ultrastable Microbubbles With Graphene Aerogel Enrichment and Machine Learning for Highly Efficient Carbon Storage

open access: yesElectron, EarlyView.
This study aims to introduce a novel‐designed structure of the colloidal aphron microbubbles reinforced by incorporating hydrophobic aerographene microparticles onto the hydrophobic outer shell. This results in the formation of a robust composite film and armored microbubble that offers exceptional ultrastability under elevated pressures of up to 400 ...
Mohammad Hossein Akhlaghi   +4 more
wiley   +1 more source

An algorithm for seizure detection in rodents

open access: yesEpilepsia Open, EarlyView.
Abstract Objective Epilepsy animal research often relies on long‐term intracranial electroencephalographic (iEEG) recordings. Here, we describe an artificial neural network (ANN) algorithm for automatic detection of seizures. Methods The algorithm was trained on iEEG recordings of three mouse models of chronic epilepsy: (1) the pilocarpine model of ...
Lyna Kamintsky   +9 more
wiley   +1 more source

Learning Rocking Dynamics From Sparse Shake‐Table Data With Interpretable Physics‐Informed Neural Networks

open access: yesEarthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT We present a hybrid interpretable Physics‐Informed Neural Network Long‐Short Term Memory (Hybrid PINN LSTM) framework for predicting the seismic response of rocking blocks. Existing analytical models rely on uncertain idealizations, while purely data‐driven and machine‐learning approaches lack physical consistency and interpretability.
Shirley Shen   +1 more
wiley   +1 more source

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