[HTML][HTML] Materials discovery and design using machine learning
Y Liu, T Zhao, W Ju, S Shi - Journal of Materiomics, 2017 - Elsevier
The screening of novel materials with good performance and the modelling of quantitative
structure-activity relationships (QSARs), among other issues, are hot topics in the field of …
structure-activity relationships (QSARs), among other issues, are hot topics in the field of …
[HTML][HTML] Emerging artificial intelligence in piezoelectric and triboelectric nanogenerators
P Jiao - Nano Energy, 2021 - Elsevier
Piezoelectric nanogenerators (PENG) and triboelectric nanogenerators (TENG) have
opened an exciting venue to sustainably harvest electrical energy from the environments …
opened an exciting venue to sustainably harvest electrical energy from the environments …
Artificial intelligence-enabled smart mechanical metamaterials: advent and future trends
Mechanical metamaterials have opened an exciting venue for control and manipulation of
architected structures in recent years. Research in the area of mechanical metamaterials …
architected structures in recent years. Research in the area of mechanical metamaterials …
Conditions for void formation in friction stir welding from machine learning
Friction stir welded joints often contain voids that are detrimental to their mechanical
properties. Here we investigate the conditions for void formation using a decision tree and a …
properties. Here we investigate the conditions for void formation using a decision tree and a …
Morphological characterization of aggregates and agglomerates by image analysis: A systematic literature review
L Théodon, J Debayle, C Coufort-Saudejaud - Powder Technology, 2023 - Elsevier
The morphological characterization of aggregates or agglomerates using image analysis is
an increasingly active area of research, whether in the chemical, environmental or civil …
an increasingly active area of research, whether in the chemical, environmental or civil …
[HTML][HTML] A computational view on nanomaterial intrinsic and extrinsic features for nanosafety and sustainability
G Mancardi, A Mikolajczyk, VK Annapoorani, A Bahl… - Materials Today, 2023 - Elsevier
In recent years, an increasing number of diverse Engineered Nano-Materials (ENMs), such
as nanoparticles and nanotubes, have been included in many technological applications …
as nanoparticles and nanotubes, have been included in many technological applications …
Performance-oriented multistage design for multi-principal element alloys with low cost yet high efficiency
Multi-principal element alloys (MPEAs) with remarkable performances possess great
potential as structural, functional, and smart materials. However, their efficient performance …
potential as structural, functional, and smart materials. However, their efficient performance …
Pavement aggregate shape classification based on extreme gradient boosting
Aggregate plays the role of skeleton filling in asphalt pavements. The shape of the
aggregate affects the embedded structure between the aggregates, thus affecting the …
aggregate affects the embedded structure between the aggregates, thus affecting the …
An evolutionary machine learning approach for municipal solid waste generation estimation utilizing socioeconomic components
Municipal solid waste generation is an important parameter in waste management with
significant impacts on environment. There are many components directly influencing solid …
significant impacts on environment. There are many components directly influencing solid …
Optimizing biodiesel production from waste cooking oil using genetic algorithm-based support vector machines
M Corral Bobadilla, R Fernández Martínez… - Energies, 2018 - mdpi.com
The ever increasing fuel demands and the limitations of oil reserves have motivated
research of renewable and sustainable energy resources to replace, even partially, fossil …
research of renewable and sustainable energy resources to replace, even partially, fossil …