Enhancing wastewater treatment efficiency through machine learning-driven effluent quality prediction: A plant-level analysis

MAP Cechinel, J Neves, JVR Fuck… - Journal of Water …, 2024 - Elsevier
The main objective of this study was to develop, validate, and comprehend machine
learning (ML) models capable of predicting chemical oxygen demand concentration in the …

Learning material synthesis–process–structure–property relationship by data fusion: Bayesian co-regionalization N-dimensional piecewise function learning

AG Kusne, A McDannald, B DeCost - Digital Discovery, 2024 - pubs.rsc.org
Autonomous materials research labs require the ability to combine and learn from diverse
data streams. This is especially true for learning material synthesis–process–structure …

Pressure-Induced Phase Diagram and Electronic Structure Evolves during the Insulator–Metal Transition of Bulk BiFeO3

R Zhang, H Dong, M Wen, F Wu - Inorganic Chemistry, 2023 - ACS Publications
BiFeO3 is the most widely known multiferroic at room temperature, possessing both
ferroelectricity and antiferromagnetism. It has high Curie temperature and Néel temperature …

Accelerated search for new ferroelectric materials

R Frey, BF Grosso, P Fandré, B Mächler… - Physical Review …, 2023 - APS
We report the development of a combined machine learning and high-throughput density
functional theory (DFT) framework to accelerate the search for new ferroelectric materials …

Prediction of the hardest BiFeO 3 from first-principles calculations

R Zhang, L Bai, X **e, P Hu, Z Wu, H Dong… - Physical Chemistry …, 2023 - pubs.rsc.org
BiFeO3 is the only material with ferroelectric Curie temperature and Néel temperature higher
than room temperature, making it one of the most well-studied multiferroic materials. Based …