Targeted design of advanced electrocatalysts by machine learning

L Chen, X Zhang, A Chen, S Yao, X Hu… - Chinese Journal of …, 2022 - Elsevier
Exploring the production and application of clean energy has always been the core of
sustainable development. As a clean and sustainable technology, electrocatalysis has been …

Uranium and lithium extraction from seawater: challenges and opportunities for a sustainable energy future

YJ Lim, K Goh, A Goto, Y Zhao, R Wang - Journal of Materials …, 2023 - pubs.rsc.org
Amid the global call for decarbonization efforts, uranium and lithium are two important metal
resources critical for securing a sustainable energy future. Extraction of uranium and lithium …

High‐throughput discovery of novel cubic crystal materials using deep generative neural networks

Y Zhao, M Al‐Fahdi, M Hu, EMD Siriwardane… - Advanced …, 2021 - Wiley Online Library
High‐throughput screening has become one of the major strategies for the discovery of
novel functional materials. However, its effectiveness is severely limited by the lack of …

On-the-fly interpretable machine learning for rapid discovery of two-dimensional ferromagnets with high Curie temperature

S Lu, Q Zhou, Y Guo, J Wang - Chem, 2022 - cell.com
Machine learning (ML) techniques have accelerated the discovery of new materials.
However, challenges such as data scarcity, representations without deep physical insights …

Machine learning for materials discovery: Two-dimensional topological insulators

GR Schleder, B Focassio, A Fazzio - Applied Physics Reviews, 2021 - pubs.aip.org
One of the main goals and challenges of materials discovery is to find the best candidates
for each interest property or application. Machine learning rises in this context to efficiently …

Graphene nanoparticles as data generating digital materials in industry 4.0

MA Ali, MS Irfan, T Khan, MY Khalid, R Umer - Scientific Reports, 2023 - nature.com
One of the potential applications of 2D materials is to enhance multi-functionality of
structures and components used in aerospace, automotive, civil and defense industries …

Omnichannel retailing: does it empower consumers and influence patronage?

S Mishra, G Malhotra, V Arora… - International Journal of …, 2022 - emerald.com
Purpose This study analyzes how omnichannel integration influences customer patronage
intention, highlighting the moderation effect of consumer service experience consciousness …

High-throughput computational discovery and intelligent design of two-dimensional functional materials for various applications

L Shen, J Zhou, T Yang, M Yang… - Accounts of Materials …, 2022 - ACS Publications
Conspectus Novel technologies and new materials are in high demand for future various
applications to overcome the fundamental limitations of current techniques. For example, the …

[HTML][HTML] Prediction of nature of band gap of perovskite oxides (ABO3) using a machine learning approach

MN Mattur, N Nagappan, S Rath, T Thomas - Journal of Materiomics, 2022 - Elsevier
A material's electronic properties and technological utility depend on its band gap value and
the nature of band gap (ie direct or indirect). This nature of band gaps is notoriously difficult …

[HTML][HTML] Artificial intelligence and machine learning in pharmacological research: bridging the gap between data and drug discovery

S Singh, R Kumar, S Payra, SK Singh - Cureus, 2023 - ncbi.nlm.nih.gov
Artificial intelligence (AI) has transformed pharmacological research through machine
learning, deep learning, and natural language processing. These advancements have …