Sarma, D.; Pegu, D.; Saikia, U.; Sahariah, M. B.: Exploring the effect of Ti on He clustering in CuZr metallic alloy. Physica Scripta 100 (7), 075918 (2025)
Kamachali, R. D.; Wallis, T.; Ikeda, Y.; Saikia, U.; Ahmadian, A.; Liebscher, C.; Hickel, T.; Maass, R.: Giant segregation transition as origin of liquid metal embrittlement in the Fe-Zn system. Scripta Materialia 238, 115758 (2024)
Saikia, U.; Sahariah, M. B.; Dutta, B.; Pandey, R.: Structure, stability and defect energetics of interfaces formed between conventional and transformed phases in Cu–Nb layered nanocomposite. Physica Scripta 98 (6), 065959 (2023)
Scientists of the Max-Planck-Institut für Eisenforschung pioneer new machine learning model for corrosion-resistant alloy design. Their results are now published in the journal Science Advances
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one. With this project, we aim to…
Atom probe tomography (APT) provides three dimensional(3D) chemical mapping of materials at sub nanometer spatial resolution. In this project, we develop machine-learning tools to facilitate the microstructure analysis of APT data sets in a well-controlled way.
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…