Anti-corrosive potential of the sustainable corrosion inhibitors based on biomass waste: a review on preceding and perspective research
Over the past decade, green chemistry has been emphasizing the importance of
environmental sustainability and human health, aiming to minimize toxins and reducing …
environmental sustainability and human health, aiming to minimize toxins and reducing …
Generative adversarial networks (GAN) based efficient sampling of chemical composition space for inverse design of inorganic materials
A major challenge in materials design is how to efficiently search the vast chemical design
space to find the materials with desired properties. One effective strategy is to develop …
space to find the materials with desired properties. One effective strategy is to develop …
An invertible crystallographic representation for general inverse design of inorganic crystals with targeted properties
Realizing general inverse design could greatly accelerate the discovery of new materials
with user-defined properties. However, state-of-the-art generative models tend to be limited …
with user-defined properties. However, state-of-the-art generative models tend to be limited …
[HTML][HTML] Evolutionary computing and machine learning for discovering of low-energy defect configurations
M Arrigoni, GKH Madsen - Npj Computational Materials, 2021 - nature.com
Density functional theory (DFT) has become a standard tool for the study of point defects in
materials. However, finding the most stable defective structures remains a very challenging …
materials. However, finding the most stable defective structures remains a very challenging …
[PDF][PDF] Inverse design of crystals using generalized invertible crystallographic representation
Deep learning has fostered many novel applications in materials informatics. However, the
inverse design of inorganic crystals, ie generating new crystal structure with targeted …
inverse design of inorganic crystals, ie generating new crystal structure with targeted …
First‐Principle Calculations to Investigate Structural, Electronic, Elastic, Mechanical, and Optical Properties of K2CuX (X=As, Sb) Ternary Compounds
Efficient materials with good optoelectronic properties are required for the good performance
of photovoltaic devices. In this work, we present findings of a theoretical investigation of the …
of photovoltaic devices. In this work, we present findings of a theoretical investigation of the …
pyGACE: Combining the genetic algorithm and cluster expansion methods to predict the ground-state structure of systems containing point defects
Searching the most stable atomic-structure of a solid with point defects (including the
extrinsic alloying/doping elements), is one of the central issues in materials science. Both …
extrinsic alloying/doping elements), is one of the central issues in materials science. Both …
[图书][B] Estimating Directional Changes Trend Reversal in Forex Using Machine Learning
ATN Adegboye - 2022 - search.proquest.com
Most forecasting algorithms use a physical time scale data to study price movement in
financial markets by taking snapshots in fixed schedule, making the flow of time …
financial markets by taking snapshots in fixed schedule, making the flow of time …
[PDF][PDF] Research Article First-Principle Calculations to Investigate Structural, Electronic, Elastic, Mechanical, and Optical Properties of K2CuX (X= As, Sb) Ternary …
Efficient materials with good optoelectronic properties are required for the good performance
of photovoltaic devices. In this work, we present findings of a theoretical investigation of the …
of photovoltaic devices. In this work, we present findings of a theoretical investigation of the …
Accelerate Materials Development Using Machine Learning: From Photovoltaic to Other Functional Materials
R Zekun - 2021 - search.proquest.com
We have seen an urgent need to accelerate materials development during the COVID-19
pandemic. Materials development for vaccination could transform society. Meanwhile, to …
pandemic. Materials development for vaccination could transform society. Meanwhile, to …