The Computational Materials Group (CMG), led by Prof. Izabela Szlufarska and Prof. Dane Morgan, congratulates Dr. Shuguang Wei on the successful defense of his Ph.D. dissertation. Dr. Wei’s research under the supervision of Prof. Izabela …
Rising Star Award in Computational Materials Science
Dr. Chen Shen and Dr. Jun Meng have both been selected as finalists for the Fifth Rising Star Award in Computational Materials Science. Both Chen Shen and Jun Meng contributed invited review articles to the …
Machine learning tool accelerates molten salt design for next-gen energy systems
Work led by Postdoc Chen Shen and Siamak Attarian, together with Profs. Dane Morgan and Izabela Szlufarska, has resulted in the development of a machine learning–based tool called SuperSalt. This powerful framework enables accurate simulation …
Promising new ‘low-work-function’ cathode material
Work from Postdoc Md Sariful Sheikh, Staff Ryan Jacobs, and Profs Morgan and Booske illustrate new thermionic emitters and value of long-term collaboration. The new material could improve components used in satellite communications, electron microscopy …
Discovery of new Interstitial Diffusers now out in Nature Materials
We are excited to share our new Nature Materials article which discovered multiple new families of fast interstitial oxygen conductors using advanced computational techniques and experimental validations. These novel materials hold significant potential to enhance …
Prof. Szlufarska group’s study published in Nature Materials
Prof. Izabela Szlufarska’s group identified new ways for making nominally brittle materials tough through the formation of amorphous shear bands. The criteria for the design of tougher materials have been published in the journal Nature …
Prof. Szlufarska awarded TMS Brimacombe Medal
Congratulations to Prof. Izabela Szlufarska for being named 2023 Brimacombe Medalist by the The Minerals, Metals and Materials Society.
How Machine Learning is Revolutionizing Materials Science – Futurum, 2023
A pedagogical nontechnical article on machine learning in materials for elementary and high school students, with activities guidelines and fun biographical information.
Predicting reactor pressure vessel behaviour for light-water reactors
Researchers at the Universities of Wisconsin and California are integrating physics and Machine Learning to predict materials degradation in nuclear reactors.
Dr. Jun Meng wins best poster award at 2022 MRS Fall meeting
Congratulations to Dr. Jun Meng for winning the best poster award at the 2022 MRS fall meeting. The poster is entitled “Experimentally informed structure optimization of amorphous TiO2 films grown by atomic layer deposition ”. …