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Glass

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Artificial Neural Networks-Based Software for Measuring Heat Collection Rate and Heat Loss Coefficient of Water-in-Glass Evacuated Tube Solar Water Heaters.

PloS one
Measurements of heat collection rate and heat loss coefficient are crucial for the evaluation of in service water-in-glass evacuated tube solar water heaters. However, conventional measurement requires expensive detection devices and undergoes a seri...

Application of neural networks with novel independent component analysis methodologies to a Prussian blue modified glassy carbon electrode array.

Talanta
Sodium potassium absorption ratio (SPAR) is an important measure of agricultural water quality, wherein four exchangeable cations (K(+), Na(+), Ca(2+) and Mg(2+)) should be simultaneously determined. An ISE-array is suitable for this application beca...

Dicke simulators with emergent collective quantum computational abilities.

Physical review letters
Using an approach inspired from spin glasses, we show that the multimode disordered Dicke model is equivalent to a quantum Hopfield network. We propose variational ground states for the system at zero temperature, which we conjecture to be exact in t...

A high-efficient batch-recirculated photoreactor packed with immobilized TiO2-P25 nanoparticles onto glass beads for photocatalytic degradation of phenazopyridine as a pharmaceutical contaminant: artificial neural network modeling.

Water science and technology : a journal of the International Association on Water Pollution Research
In this study, removal efficiency of phenazopyridine (PhP) as a model pharmaceutical contaminant was investigated in a batch-recirculated photoreactor packed with immobilized TiO2-P25 nanoparticles on glass beads. Influence of various operational par...

Machine-Learning-Based Predictive Modeling of Glass Transition Temperatures: A Case of Polyhydroxyalkanoate Homopolymers and Copolymers.

Journal of chemical information and modeling
Polyhydroxyalkanoate-based polymers-being ecofriendly, biosynthesizable, and economically viable and possessing a broad range of tunable properties-are currently being actively pursued as promising alternatives for petroleum-based plastics. The vast ...

Machine learning as a tool to design glasses with controlled dissolution for healthcare applications.

Acta biomaterialia
The advancement of glass science has played a pivotal role in enhancing the quality and length of human life. However, with an ever-increasing demand for glasses in a variety of healthcare applications - especially with controlled degradation rates -...

PIXE based, Machine-Learning (PIXEL) supported workflow for glass fragments classification.

Talanta
This paper presents a structured workflow for glass fragment analysis based on a combination of Elemental Analysis using PIXE and Machine Learning tools, with the ultimate goal of standardizing and helping forensic efforts. The proposed workflow was ...

High-Speed Handling Robot with Bionic End-Effector for Large Glass Substrate in Clean Environment.

Sensors (Basel, Switzerland)
The development of "large display, high performance and low cost" in the FPD industry demands glass substrates to be "larger and thinner". Therefore, the requirements of handling robots are developing in the direction of large scale, high speed, and ...

Characterization of Biocomposites and Glass Fiber Epoxy Composites Based on Acoustic Emission Signals, Deep Feature Extraction, and Machine Learning.

Sensors (Basel, Switzerland)
This study presents the results of acoustic emission (AE) measurements and characterization in the loading of biocomposites at room and low temperatures that can be observed in the aviation industry. The fiber optic sensors (FOS) that can outperform ...

Predicting Dynamic Heterogeneity in Glass-Forming Liquids by Physics-Inspired Machine Learning.

Physical review letters
We introduce GlassMLP, a machine learning framework using physics-inspired structural input to predict the long-time dynamics in deeply supercooled liquids. We apply this deep neural network to atomistic models in 2D and 3D. Its performance is better...