Big-data science in porous materials: materials genomics and machine learning
By combining metal nodes with organic linkers we can potentially synthesize millions of
possible metal–organic frameworks (MOFs). The fact that we have so many materials opens …
possible metal–organic frameworks (MOFs). The fact that we have so many materials opens …
Machine learning in analytical chemistry: From synthesis of nanostructures to their applications in luminescence sensing
Over the past decade, the wide-scale adoption of artificial intelligence (AI) and machine
learning (ML) has transformed the landscape of scientific research and development, which …
learning (ML) has transformed the landscape of scientific research and development, which …
[HTML][HTML] A novel approach for estimating and predicting uncertainty in water quality index model using machine learning approaches
With the significant increase in WQI applications worldwide and lack of specific application
guidelines, accuracy and reliability of WQI models is a major issue. It has been reported that …
guidelines, accuracy and reliability of WQI models is a major issue. It has been reported that …
Best practices in machine learning for chemistry
Best practices in machine learning for chemistry | Nature Chemistry Skip to main content
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Thank you for visiting nature.com. You are using a browser version with limited support for …
[HTML][HTML] Robust machine learning algorithms for predicting coastal water quality index
Coastal water quality assessment is an essential task to keep “good water quality” status for
living organisms in coastal ecosystems. The Water quality index (WQI) is a widely used tool …
living organisms in coastal ecosystems. The Water quality index (WQI) is a widely used tool …
[HTML][HTML] Assessing optimization techniques for improving water quality model
In order to keep the" good" status of coastal water quality, it is essential to monitor and
assess frequently. The Water quality index (WQI) model is one of the most widely used …
assess frequently. The Water quality index (WQI) model is one of the most widely used …
Machine learning-assisted low-dimensional electrocatalysts design for hydrogen evolution reaction
J Li, N Wu, J Zhang, HH Wu, K Pan, Y Wang, G Liu… - Nano-Micro Letters, 2023 - Springer
Efficient electrocatalysts are crucial for hydrogen generation from electrolyzing water.
Nevertheless, the conventional" trial and error" method for producing advanced …
Nevertheless, the conventional" trial and error" method for producing advanced …
Benchmarking materials property prediction methods: the Matbench test set and Automatminer reference algorithm
We present a benchmark test suite and an automated machine learning procedure for
evaluating supervised machine learning (ML) models for predicting properties of inorganic …
evaluating supervised machine learning (ML) models for predicting properties of inorganic …
Prediction of compressive strength of geopolymer concrete using a hybrid ensemble of grey wolf optimized machine learning estimators
SK Parhi, SK Patro - Journal of Building Engineering, 2023 - Elsevier
Geopolymer concrete (GPC) has the potential to replace conventional concrete. But, the
mixed proportion of GPC poses several difficulties due to various contributing factors. The …
mixed proportion of GPC poses several difficulties due to various contributing factors. The …
Machine learning (ML) in medicine: Review, applications, and challenges
AM Rahmani, E Yousefpoor, MS Yousefpoor… - Mathematics, 2021 - mdpi.com
Today, artificial intelligence (AI) and machine learning (ML) have dramatically advanced in
various industries, especially medicine. AI describes computational programs that mimic and …
various industries, especially medicine. AI describes computational programs that mimic and …