En Ma

Phase Change and Memory


Xi'an Jiaotong University, Xi’an, China


Email: maen@xjtu.edu.cn



      En Ma is a professor at School of Materials Science and Engineering, Xi'an Jiaotong University. He received his Ph.D. degree from Tsinghua University in 1989. He was a professor of Materials Science and Engineering at Johns Hopkins University from 1998 to 2020. In 2021, he established the Center for Alloy Innovation and Design (CAID) with the support of State Key Laboratory for Mechanical Behavior of Materials at XJTU. He is an elected Fellow of the Materials Research Society, ASM International, and the American Physical Society. His research interest includes chalcogenide phase-change alloys, metallic glasses, high-entropy alloys, and mechanical properties of nanostructured materials. He has published approximately 400 archival papers, with more than 50,500 citations (H index = 115), and presented approximately 250 invited talks at international conferences and seminars.


Abstract for Presentation

Phase-change memory materials by design



   The global demand for data storage and processing has increased exponentially in recent decades. Non-volatile memory technologies combine the advantages of persistent storage and fast operation speed, which greatly improve the memory hierarchy for better computing and power efficiencies. Chalcogenide phase-change materials (PCMs) are leading candidates for non-volatile memory devices.[1] The PCM-based products, such as Intel Optane memory, have entered the global memory market as storage-class memory (SCM). PCM exploits the large contrast in electrical resistance between its amorphous state (logic state = 0) and crystalline state (logical state = 1) to store data. The fast and reversible phase transition at elevated temperatures and yet good thermal stability of the two states at room temperature guarantees both high operation speed and long-term data storage. This talk discusses the microscopic mechanisms of the structural transition, electrical contrast, resistance drift, and power consumption of phase-change memory. In particular, I will highlight the power of materials design and engineering in elevating the performance of PCM-based memory in neuro-inspired computing technologies.[2-4]





[1] W. Zhang, R. Mazzarello, M. Wuttig, E. Ma, Nat. Rev. Mater. 4 (2019) 150.
[2] F. Rao, K. Ding, Y. Zhou, Y. Zheng, M. Xia, S. Lv, Z. Song, S. Feng, I. Ronneberger, R. Mazzarello, W. Zhang, E. Ma, Science, 358 (2017) 1423.
[3] K. Ding, J. Wang, Y. Zhou, H. Tian, L. Lu, R. Mazzarello, C. Jia, W. Zhang, F. Rao, E. Ma, Science, 366 (2019) 210.
[4] Z. Yang, B. Li, J.-J. Wang, X.-D. Wang, M. Xu, H. Tong, X. Cheng, L. Lu, C. Jia, M. Xu, X. Miao, W. Zhang, E. Ma, Adv. Sci. 9 (2022) 2103478