Machine learning for high-entropy alloys: Progress, challenges and opportunities
High-entropy alloys (HEAs) have attracted extensive interest due to their exceptional
mechanical properties and the vast compositional space for new HEAs. However …
mechanical properties and the vast compositional space for new HEAs. However …
The integral role of high‐entropy alloys in advancing solid‐state hydrogen storage
High‐entropy alloys (HEAs) have emerged as a groundbreaking class of materials poised to
revolutionize solid‐state hydrogen storage technology. This comprehensive review delves …
revolutionize solid‐state hydrogen storage technology. This comprehensive review delves …
Extracting accurate materials data from research papers with conversational language models and prompt engineering
There has been a growing effort to replace manual extraction of data from research papers
with automated data extraction based on natural language processing, language models …
with automated data extraction based on natural language processing, language models …
Predicting materials properties without crystal structure: deep representation learning from stoichiometry
Abstract Machine learning has the potential to accelerate materials discovery by accurately
predicting materials properties at a low computational cost. However, the model inputs …
predicting materials properties at a low computational cost. However, the model inputs …
High temperature strength of refractory complex concentrated alloys
Thermodynamic and mechanical properties of 15 single-phase and 11 multi-phase
refractory complex concentrated alloys (RCCAs) are reported. Using the CALPHAD …
refractory complex concentrated alloys (RCCAs) are reported. Using the CALPHAD …
Machine-learning and high-throughput studies for high-entropy materials
The combination of multiple-principal element materials, known as high-entropy materials
(HEMs), expands the multi-dimensional compositional space to gigantic stoichiometry. It is …
(HEMs), expands the multi-dimensional compositional space to gigantic stoichiometry. It is …
High-entropy perovskites: An emergent class of oxide thermoelectrics with ultralow thermal conductivity
R Banerjee, S Chatterjee, M Ranjan… - ACS Sustainable …, 2020 - ACS Publications
Although SrTiO3-based perovskites showed a lot of promise as n-type thermoelectric (TE)
materials, they demonstrated a low figure of merit value primarily because of their high …
materials, they demonstrated a low figure of merit value primarily because of their high …
Machine learning of phases and mechanical properties in complex concentrated alloys
The mechanical properties of complex concentrated alloys (CCAs) depend on their formed
phases and corresponding microstructures. The data-driven prediction of the phase …
phases and corresponding microstructures. The data-driven prediction of the phase …
Machine learning approach to predict new multiphase high entropy alloys
YV Krishna, UK Jaiswal, MR Rahul - Scripta Materialia, 2021 - Elsevier
High entropy alloys with multi-principal elements have interested the research community
due to the promising properties and tunable microstructure. In the current study, the …
due to the promising properties and tunable microstructure. In the current study, the …
Machine learning paves the way for high entropy compounds exploration: challenges, progress, and outlook
Abstract Machine learning (ML) has emerged as a powerful tool in the research field of high
entropy compounds (HECs), which have gained worldwide attention due to their vast …
entropy compounds (HECs), which have gained worldwide attention due to their vast …