The data-driven approach has recently emerged as a viable alternative strategy for the design of complex metallic alloys. In fact, machine learning (ML) is thought to have the potential to propel materials informatics to the forefront. ML enables estimations primarily based on available data, eliminating the need for lengthy experimentation or molecular and atomistic simulations. Keeping in mind the unravelled potential of ML in materials discovery, several studies have been performed at the Solidification and Nanomaterials Lab, Indian Institute of Technology Kanpur to design and develop advanced materials including high entropy ceramics, multi-principal multicomponent alloys and multicomponent metallic glasses.

Related Publications:

1. Anurag Bajpai, Ziyuan Rao, Abhinav Dixit, Krishanu Biswas and Dierk Raabe; Interpretable Machine Learning for High-Strength High-Entropy Alloy Design (under review, Science, 2024, Manuscript Number: adt0993).

2. Anurag Bajpai and Dierk Raabe; Data-Driven Interpretation for Glass-Forming Ability of Multicomponent Metallic Glasses through Dimensionally Accurate Symbolic Regression (under review, npj Computational Materials, 2025).

3. Anurag Bajpai and Dierk Raabe; Exploring Latent Design Spaces: A Variational Information Bottleneck and Attention-Driven Framework for Hardness Optimization in Multicomponent Amorphous Alloys (under review, Materials Research Letters, 2025).

4. Ziyuan Rao*, Anurag Bajpai* (*equal contribution), Hongbin Zhang; Active Learning Strategies for design of Sustainable Alloys (Invited Article), Philosophical Transactions of the Royal Society–A, 2024, DOI: https://doi.org/10.1098/rsta.2023.0242).

5. Anurag Bajpai, Jatin Bhatt, Krishanu Biswas and Nilesh P. Gurao; Accelerated design of Multicomponent Metallic Glasses using Machine Learning; Journal of Materials Research; Volume 37; 2022 (DOI: https://doi.org/10.1557/s43578-022-00659-2).

6. Anurag Bajpai, Jatin Bhatt, Krishanu Biswas and Nilesh P. Gurao; A new approach to design Multicomponent Metallic Glasses using Mendeleev Number; Philosophical Magazine; 2022 (DOI: https://doi.org/10.1080/14786435.2022.2121868).

7. Anurag Bajpai, Jatin Bhatt, Krishanu Biswas and Nilesh P. Gurao; A new perspective to thermodynamical designing of high entropy bulk metallic glasses (HE-BMGs); Physica B: Condensed Matter; Volume 595; 2020 (DOI: https://doi.org/10.1016/j.physb.2020.412350).

8. Rahul Mitra, Anurag Bajpai, and Krishanu Biswas; ADASYN-assisted machine learning for phase prediction of high entropy carbides; Computational Materials Science; Volume 223; 2023 (DOI: https://doi.org/10.1016/j.commatsci.2023.112142). 

9. Rahul Mitra, Anurag Bajpai, and Krishanu Biswas; Machine learning-based approach for phase prediction in High Entropy Borides; Ceramics International; Volume 48; 2022 (DOI: https://doi.org/10.1016/j.ceramint.2022.02.218).

10. Bejjipurapu Akhil, Anurag Bajpai, N. P. Gurao and Krishanu Biswas; Designing Hexagonal Close Packed High Entropy Alloys using Machine Learning; Modelling and Simulation in Materials Science and Engineering; Volume 29; 2021 (DOI: https://doi.org/10.1088/1361-651X/ac2b37).

Ongoing Project: Presently, at Max-Planck-Institut für Eisenforschung, Germany (MPIE), we are aiming to develop robust machine learning-based design methodologies to develop advanced steels from steel scrap using a combination of interpretable machine learning and active learning. Additionally, we are trying to understand the balance between exploitation and exploration strategies for materials discovery, while attempting to unveil the so-called "black box" nature of machine learning models. (Project inception - 2023)

Related Publications: (coming soon)

Multicomponent alloys are a fascinating class of new materials. These include both crystalline as well as amorphous multicomponent alloys. What makes them even more fascinating is the evolution of their properties depending upon their micro and atomic structures, allowing customization for desired attributes. Therefore, we attempt to understand the intricate relationship between their structure and the resulting thermal, mechanical and functional properties.

Related Publications:

1. Anurag Bajpai and Krishanu Biswas; Thermal Stability of newly developed Cu-Zr-Ag-Ti-Ni Multicomponent Bulk Metallic Glass; Materials Chemistry and Physics; Volume 307; 2023 (DOI: https://doi.org/10.1016/j.matchemphys.2023.128092).

2. S. S. Mishra, Anurag Bajpai, Krishanu Biswas et al.; An Experimental and Theoretical Investigation on Structure-Property Correlation of Cu2Mn1Al1-xGax Full-Heusler Alloy; Journal of Alloys and Compounds; Volume 898; 2021 (DOI: https://doi.org/10.1016/j.jallcom.2021.162865).

3. S. S. Mishra, Anurag Bajpai, Krishanu Biswas; TiVCrNiZrFex High entropy alloy: Phase evolution, Magnetic and Mechanical properties; Journal of Alloys and Compounds; Volume 871; 2021 (DOI: https://doi.org/10.1016/j.jallcom.2021.159572).

4. Bejjipurapu Akhil, Anurag Bajpai and Krishanu Biswas; Microstructure and Mechanical Properties of the new TiZrHfReAl HCP High Entropy alloy; Philosophical Magazine Letters; 2022 (DOI: https://doi.org/10.1080/09500839.2022.2120644).

5. Jitesh Kumar, Saumya Jha, Abheepsit Raturi, Anurag Bajpai, Reshma Sonkusare, NP Gurao, Krishanu Biswas; Novel Alloy Design Concepts Enabling Enhanced Mechanical Properties of High Entropy Alloys; Frontiers in Materials; Volume 9; 2022 (DOI: https://doi.org/10.3389/fmats.2022.868721).

Ongoing Project: Presently, we are trying to understand the role of local short-range order in the evolution of thermal and mechanical properties of amorphous multicomponent alloys through a combination of high-resolution experimental techniques and theory. 

Related Publications: (coming soon)

Material Beneficiation from Electronic Waste 

Electronic waste has emerged as the world's fastest-growing waste source in recent decades. The global accumulation of e-waste is expected to reach 74 Mt by 2030, nearly doubling in tonnage over the next decade. Since e-waste has dramatically increased the impact on the environment, developing sustainable solutions for e-waste recovery and recycling is of vital importance. In this direction, we at Solidification and Nanomaterials Lab,  Indian Institute of Technology Kanpur aim to establish easily scalable new green ways to rejuvenate and effectively use critical materials components (common metals, rare earths and polymer) of e-waste using a confluence of metallurgy and green chemistry. 

Related Publications:

1. Shruti Srivastava, Anurag Bajpai, and Krishanu Biswas; Recovery of Rare Earth Elements (Nd, Dy) from spent magnets using EDTA Functionalized Chitosan; RSC Sustainability; Volume 2; 2024 (https://doi.org/10.1039/D3SU00427A).

2. Anurag Bajpai, Partha Kumbhakar, Chandra Sekhar Tiwary and Krishanu Biswas; Conducting graphene synthesis from electronic waste; ACS Sustainable Chemistry and Engineering; Volume 42; 2021 (DOI: https://doi.org/10.1021/acssuschemeng.1c03817).

3. Nidhi Sharma*, Anurag Bajpai* (*equal contribution), Chandra Sekhar Tiwary, and Krishanu Biswas et al.; Green Route for Beneficiation of Metallic Materials from Electronic Waste for Selective Reduction of CO2; ACS Sustainable Chemistry and Engineering; Volume 32; 2020 (DOI: https://doi.org/10.1021/acssuschemeng.0c03605).

Green Manganese from Low-grade manganese ores

Ongoing Project: Presently, at Max-Planck-Institut für Eisenforschung, Germany (MPIE), we are now trying to understand the micro-mechanisms dictating the reduction of Manganese oxide ores to green Manganese through hydrogen reduction. With a pan-Europe collaborative network, we aim to develop and demonstrate an integrated sustainable process to produce manganese (Mn) and Mn alloys from Mn ores and Mn-containing byproducts and waste by using hydrogen and secondary aluminium sources as reductants. (Project inception - 2023)

Related Publications: (coming soon)